{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,8]],"date-time":"2026-08-08T18:21:10Z","timestamp":1786213270001,"version":"3.56.0"},"reference-count":195,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2024,9,30]],"date-time":"2024-09-30T00:00:00Z","timestamp":1727654400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2024,9,30]],"date-time":"2024-09-30T00:00:00Z","timestamp":1727654400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Artif Intell Rev"],"DOI":"10.1007\/s10462-024-10944-7","type":"journal-article","created":{"date-parts":[[2024,9,30]],"date-time":"2024-09-30T08:03:02Z","timestamp":1727683382000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":221,"title":["A systematic review of deep learning techniques for plant diseases"],"prefix":"10.1007","volume":"57","author":[{"given":"Ishak","family":"Pacal","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ismail","family":"Kunduracioglu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mehmet Hakki","family":"Alma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muhammet","family":"Deveci","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seifedine","family":"Kadry","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jan","family":"Nedoma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vlastimil","family":"Slany","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Radek","family":"Martinek","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,9,30]]},"reference":[{"key":"10944_CR1","doi-asserted-by":"publisher","first-page":"106279","DOI":"10.1016\/j.compag.2021.106279","volume":"187","author":"A Abbas","year":"2021","unstructured":"Abbas A, Jain S, Gour M, Vankudothu S (2021) Tomato plant disease detection using transfer learning with C-GAN synthetic images. Comput Electron Agric 187:106279","journal-title":"Comput Electron Agric"},{"issue":"3","key":"10944_CR2","doi-asserted-by":"publisher","first-page":"2246","DOI":"10.1080\/03772063.2019.1696716","volume":"68","author":"S Abisha","year":"2022","unstructured":"Abisha S, Jayasree T (2022) Application of image processing techniques and artificial neural network for detection of diseases on brinjal leaf. IETE J Res 68(3):2246\u20132258","journal-title":"IETE J Res"},{"key":"10944_CR3","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1186\/s13640-023-00618-9","volume":"1","author":"LM Abouelmagd","year":"2024","unstructured":"Abouelmagd LM, Shams MY, Marie HS, Hassanien AE (2024) An optimized capsule neural networks for tomato leaf disease classification. EURASIP J Image Video Process 1:2","journal-title":"EURASIP J Image Video Process"},{"issue":"3","key":"10944_CR4","doi-asserted-by":"publisher","first-page":"605","DOI":"10.1007\/s41348-022-00583-x","volume":"129","author":"E Acar","year":"2022","unstructured":"Acar E, Ertugrul OF, Aldemir E, Oztekin A (2022) Automatic identification of cassava leaf diseases utilizing morphological hidden patterns and multi-feature textures with a distributed structure-based classification approach. J Plant Dis Prot 129(3):605\u2013621","journal-title":"J Plant Dis Prot"},{"issue":"1","key":"10944_CR5","doi-asserted-by":"publisher","first-page":"28","DOI":"10.3390\/plants10010028","volume":"10","author":"A Afifi","year":"2020","unstructured":"Afifi A, Alhumam A, Abdelwahab A (2020) Convolutional neural network for automatic identification of plant diseases with limited data. Plants 10(1):28","journal-title":"Plants"},{"key":"10944_CR6","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1016\/j.procs.2020.03.225","volume":"167","author":"M Agarwal","year":"2020","unstructured":"Agarwal M, Singh A, Arjaria S, Sinha A, Gupta S (2020) ToLeD: Tomato leaf disease detection using convolution neural network. Procedia Comput Sci 167:293\u2013301","journal-title":"Procedia Comput Sci"},{"issue":"19","key":"10944_CR8","doi-asserted-by":"publisher","first-page":"5569","DOI":"10.3390\/s20195569","volume":"20","author":"J Ahmad","year":"2020","unstructured":"Ahmad J, Jan B, Farman H, Ahmad W, Ullah A (2020) Disease detection in plum using convolutional neural network under true field conditions. Sensors 20(19):5569","journal-title":"Sensors"},{"key":"10944_CR7","first-page":"1","volume":"2020","author":"I Ahmad","year":"2020","unstructured":"Ahmad I, Hamid M, Yousaf S, Shah ST, Ahmad MO (2020a) Optimizing pretrained convolutional neural networks for tomato leaf disease detection. Complexity 2020:1\u20136","journal-title":"Complexity"},{"issue":"3","key":"10944_CR9","doi-asserted-by":"publisher","first-page":"478","DOI":"10.3390\/agriengineering3030032","volume":"3","author":"AA Ahmed","year":"2021","unstructured":"Ahmed AA, Reddy GH (2021) A mobile-based system for detecting plant leaf diseases using deep learning. AgriEngineering 3(3):478\u2013493","journal-title":"AgriEngineering"},{"key":"10944_CR10","doi-asserted-by":"crossref","unstructured":"Akshai KP, Anitha J (2021) Plant disease classification using deep learning. In: 2021 3rd International conference on signal processing and communication (ICPSC). IEEE, pp 407\u2013411","DOI":"10.1109\/ICSPC51351.2021.9451696"},{"issue":"11","key":"10944_CR11","doi-asserted-by":"publisher","first-page":"5206","DOI":"10.3390\/s23115206","volume":"23","author":"MEE Alahi","year":"2023","unstructured":"Alahi MEE, Sukkuea A, Tina FW, Nag A, Kurdthongmee W, Suwannarat K, Mukhopadhyay SC (2023) Integration of IoT-enabled technologies and artificial intelligence (AI) for smart city scenario: recent advancements and future trends. Sensors 23(11):5206","journal-title":"Sensors"},{"key":"10944_CR12","doi-asserted-by":"crossref","unstructured":"Albattah W, Nawaz M, Javed A, Masood M, Albahli S (2022) A novel deep learning method for detection and classification of plant diseases. Complex Intell Syst pp 1\u201318","DOI":"10.1007\/s40747-021-00536-1"},{"key":"10944_CR13","doi-asserted-by":"publisher","first-page":"124363","DOI":"10.1109\/ACCESS.2022.3220234","volume":"10","author":"Q An","year":"2022","unstructured":"An Q, Wang K, Li Z, Song C, Tang X, Song J (2022) Real-time monitoring method of strawberry fruit growth state based on YOLO improved model. IEEE Access 10:124363\u2013124372","journal-title":"IEEE Access"},{"issue":"2","key":"10944_CR14","doi-asserted-by":"publisher","first-page":"469","DOI":"10.3390\/app10020469","volume":"10","author":"A Anagnostis","year":"2020","unstructured":"Anagnostis A, Asiminari G, Papageorgiou E, Bochtis D (2020) A convolutional neural networks based method for anthracnose infected walnut tree leaves identification. Appl Sci 10(2):469","journal-title":"Appl Sci"},{"issue":"2","key":"10944_CR15","first-page":"338","volume":"12","author":"S Anand","year":"2024","unstructured":"Anand S, Pillai B, Gupta N (2024) Identification of potato plant diseases using deep neural network model and image segmentation. Int J Innov Res Technol Sci 12(2):338\u2013344","journal-title":"Int J Innov Res Technol Sci"},{"issue":"2","key":"10944_CR16","doi-asserted-by":"publisher","first-page":"757","DOI":"10.1007\/s00521-023-09058-y","volume":"36","author":"AD Andrushia","year":"2024","unstructured":"Andrushia AD, Neebha TM, Patricia AT, Sagayam KM, Pramanik S (2024) Capsule network-based disease classification for Vitis vinifera leaves. Neural Comput Appl 36(2):757\u2013772","journal-title":"Neural Comput Appl"},{"key":"10944_CR17","doi-asserted-by":"publisher","first-page":"100178","DOI":"10.1016\/j.atech.2023.100178","volume":"4","author":"AO Anim-Ayeko","year":"2023","unstructured":"Anim-Ayeko AO, Schillaci C, Lipani A (2023) Automatic blight disease detection in potato (Solanum tuberosum L.) and tomato (Solanum lycopersicum\u00a0L. 1753) plants using deep learning. Smart Agric Technol 4:100178","journal-title":"Smart Agric Technol"},{"key":"10944_CR18","doi-asserted-by":"publisher","first-page":"105542","DOI":"10.1016\/j.compag.2020.105542","volume":"175","author":"D Arg\u00fceso","year":"2020","unstructured":"Arg\u00fceso D, Picon A, Irusta U, Medela A, San-Emeterio MG, Bereciartua A, Alvarez-Gila A (2020) Few-shot learning approach for plant disease classification using images taken in the field. Comput Electron Agric 175:105542","journal-title":"Comput Electron Agric"},{"issue":"2","key":"10944_CR19","first-page":"877","volume":"15","author":"S Arjunagi","year":"2023","unstructured":"Arjunagi S, Patil NB (2023) Optimized convolutional neural network for identification of maize leaf diseases with adaptive ageist spider monkey optimization model. Int J Inform Technol 15(2):877\u2013891","journal-title":"Int J Inform Technol"},{"key":"10944_CR20","first-page":"480","volume":"51","author":"S Ashwinkumar","year":"2022","unstructured":"Ashwinkumar S, Rajagopal S, Manimaran V, Jegajothi B (2022) Automated plant leaf disease detection and classification using optimal MobileNet based convolutional neural networks. Mater Today: Proc 51:480\u2013487","journal-title":"Mater Today: Proc"},{"key":"10944_CR21","doi-asserted-by":"publisher","first-page":"1","DOI":"10.59543\/comdem.v1i.10039","volume":"1","author":"E Aslan","year":"2024","unstructured":"Aslan E, \u00d6Z\u00dcPAK Y (2024) Diagnosis and accurate classification of apple leaf diseases using Vision transformers. Comput Decis Making: Int J 1:1\u201312","journal-title":"Comput Decis Making: Int J"},{"key":"10944_CR22","doi-asserted-by":"publisher","first-page":"101182","DOI":"10.1016\/j.ecoinf.2020.101182","volume":"61","author":"\u00dc Atila","year":"2021","unstructured":"Atila \u00dc, U\u00e7ar M, Akyol K, U\u00e7ar E (2021) Plant leaf disease classification using EfficientNet deep learning model. Ecol Inf 61:101182","journal-title":"Ecol Inf"},{"issue":"1","key":"10944_CR23","first-page":"012072","volume":"1751","author":"HR Ayu","year":"2021","unstructured":"Ayu HR, Surtono A, Apriyanto DK (2021) Deep learning for detection cassava leaf disease. J Phys: Conf Ser 1751(1):012072","journal-title":"J Phys: Conf Ser"},{"issue":"4","key":"10944_CR24","doi-asserted-by":"publisher","first-page":"799","DOI":"10.62110\/sciencein.jist.2024.v12.799","volume":"12","author":"S Banarase","year":"2024","unstructured":"Banarase S, Shirbahadurkar S (2024) The Orchard Guard: deep learning powered apple leaf disease detection with MobileNetV2 model. J Integr Sci Technol 12(4):799\u2013799","journal-title":"J Integr Sci Technol"},{"key":"10944_CR25","doi-asserted-by":"publisher","first-page":"e432","DOI":"10.7717\/peerj-cs.432","volume":"7","author":"BS Bari","year":"2021","unstructured":"Bari BS, Islam MN, Rashid M, Hasan MJ, Razman MAM, Musa RM, Nasir AFA, Majeed APA (2021) A real-time approach of diagnosing rice leaf disease using deep learning-based faster R-CNN framework. PeerJ Comput Sci 7:e432","journal-title":"PeerJ Comput Sci"},{"issue":"2","key":"10944_CR26","doi-asserted-by":"publisher","first-page":"392","DOI":"10.1016\/j.gltp.2021.10.004","volume":"3","author":"U Barman","year":"2022","unstructured":"Barman U, Choudhury RD (2022) Smartphone assist deep neural network to detect the citrus diseases in agri-informatics. Global Transit Proc 3(2):392\u2013398","journal-title":"Global Transit Proc"},{"key":"10944_CR27","doi-asserted-by":"publisher","first-page":"106066","DOI":"10.1016\/j.compag.2021.106066","volume":"183","author":"H Bazame","year":"2021","unstructured":"Bazame H, Molin JP, Althoff D, Martello M (2021) Detection, classification, and mapping of coffee fruits during harvest with computer vision. Comput Electron Agric 183:106066","journal-title":"Comput Electron Agric"},{"key":"10944_CR28","first-page":"90","volume":"5","author":"P Bedi","year":"2021","unstructured":"Bedi P, Gole P (2021) Plant disease detection using hybrid model based on convolutional autoencoder and convolutional neural network. Artif Intell Agric 5:90\u2013101","journal-title":"Artif Intell Agric"},{"key":"10944_CR29","doi-asserted-by":"crossref","unstructured":"Bi C, Wang J, Duan Y, Fu B, Kang JR, Shi Y (2022) MobileNet based apple leaf diseases identification. Mob Netw Appl 1\u20139","DOI":"10.1007\/s11036-020-01640-1"},{"key":"10944_CR30","doi-asserted-by":"crossref","unstructured":"Biswas S, Saha I, Deb A (2024) Plant disease identification using a novel time-effective CNN architecture. Multimedia Tools Appl, 1\u201323","DOI":"10.1007\/s11042-024-18822-8"},{"key":"10944_CR31","doi-asserted-by":"crossref","unstructured":"Brindha GM, Karishma KK, Nivetha J, Vidhya B (2022) Automatic detection of citrus fruit diseases using mib classifier. In 2022 3rd International conference on electronics and sustainable communication systems (ICESC). IEEE, pp 1111\u20131116","DOI":"10.1109\/ICESC54411.2022.9885702"},{"key":"10944_CR32","unstructured":"Butt N, Iqbal MM, Ahmad I, Akbar H, Khadam U (2024) Citrus diseases detection using deep learning. J Comput Biomed Inform, 23\u201333"},{"key":"10944_CR33","first-page":"213","volume-title":"European conference on computer vision","author":"N Carion","year":"2020","unstructured":"Carion N, Massa F, Synnaeve G, Usunier N, Kirillov A, Zagoruyko S (2020) End-to-end object detection with transformers. European conference on computer vision. Springer, Cham, pp 213\u2013229"},{"issue":"3","key":"10944_CR34","doi-asserted-by":"publisher","first-page":"573","DOI":"10.1007\/s13562-021-00732-7","volume":"31","author":"S Chakraborty","year":"2022","unstructured":"Chakraborty S, Kodamana H, Chakraborty S (2022) Deep learning aided automatic and reliable detection of tomato begomovirus infections in plants. J Plant Biochem Biotechnol 31(3):573\u2013580","journal-title":"J Plant Biochem Biotechnol"},{"key":"10944_CR37","unstructured":"Chen Y, Kalantidis Y, Li J, Yan S, Feng J (2018) A^ 2-nets: double attention networks. Advances in neural information processing systems, p 31"},{"key":"10944_CR35","doi-asserted-by":"publisher","first-page":"105393","DOI":"10.1016\/j.compag.2020.105393","volume":"173","author":"J Chen","year":"2020","unstructured":"Chen J, Chen J, Zhang D, Sun Y, Nanehkaran YA (2020) Using deep transfer learning for image-based plant disease identification. Comput Electron Agric 173:105393","journal-title":"Comput Electron Agric"},{"key":"10944_CR36","doi-asserted-by":"publisher","first-page":"107901","DOI":"10.1016\/j.asoc.2021.107901","volume":"113","author":"J Chen","year":"2021","unstructured":"Chen J, Zhang D, Suzauddola M, Zeb A (2021a) Identifying crop diseases using attention embedded MobileNet-V2 model. Appl Soft Comput 113:107901","journal-title":"Appl Soft Comput"},{"key":"10944_CR38","first-page":"1","volume":"2021","author":"W Chen","year":"2021","unstructured":"Chen W, Zhang J, Guo B, Wei Q, Zhu Z (2021b) An apple detection method based on Des-YOLO v4 algorithm for harvesting robots in complex environment. Math Prob Eng 2021:1\u201312","journal-title":"Math Prob Eng"},{"key":"10944_CR39","doi-asserted-by":"crossref","unstructured":"Chen Z, Su R, Wang Y, Chen G, Wang Z, Yin P, Wang J (2022) Automatic estimation of apple orchard blooming levels using the improved YOLOv5. Agronomy, 12(10)","DOI":"10.3390\/agronomy12102483"},{"key":"10944_CR40","first-page":"909","volume":"9","author":"M Chohan","year":"2020","unstructured":"Chohan M, Khan A, Chohan R, Hassan S, Mahar M (2020) Plant disease detection using deep learning. Int J Recent Technol Eng 9:909\u2013914","journal-title":"Int J Recent Technol Eng"},{"key":"10944_CR41","doi-asserted-by":"crossref","unstructured":"Chollet F (2017) Xception: Deep learning with depthwise separable convolutions. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp 1251\u20131258","DOI":"10.1109\/CVPR.2017.195"},{"key":"10944_CR42","doi-asserted-by":"crossref","unstructured":"Chougui A, Moussaoui A, Moussaoui A (2022) Plant-leaf diseases classification using cnn, cbam and vision transformer. In: 2022 5th International symposium on informatics and its applications (ISIA). IEEE, pp 1\u20136","DOI":"10.1109\/ISIA55826.2022.9993601"},{"issue":"2","key":"10944_CR43","doi-asserted-by":"publisher","first-page":"294","DOI":"10.3390\/agriengineering3020020","volume":"3","author":"ME Chowdhury","year":"2021","unstructured":"Chowdhury ME, Rahman T, Khandakar A, Ayari MA, Khan AU, Khan MS, Al-Emadi N, Reaz M, Islam M, Ali S (2021) Automatic and reliable leaf disease detection using deep learning techniques. AgriEngineering 3(2):294\u2013312","journal-title":"AgriEngineering"},{"key":"10944_CR44","doi-asserted-by":"publisher","first-page":"108481","DOI":"10.1016\/j.compag.2023.108481","volume":"216","author":"G Dai","year":"2024","unstructured":"Dai G, Tian Z, Fan J, Sunil CK, Dewi C (2024) DFN-PSAN: multi-level deep information feature fusion extraction network for interpretable plant disease classification. Comput Electron Agric 216:108481","journal-title":"Comput Electron Agric"},{"key":"10944_CR45","doi-asserted-by":"publisher","first-page":"100616","DOI":"10.1016\/j.swevo.2019.100616","volume":"52","author":"A Darwish","year":"2020","unstructured":"Darwish A, Ezzat D, Hassanien AE (2020) An optimized model based on convolutional neural networks and orthogonal learning particle swarm optimization algorithm for plant diseases diagnosis. Swarm Evol Comput 52:100616","journal-title":"Swarm Evol Comput"},{"key":"10944_CR46","doi-asserted-by":"crossref","unstructured":"Das D, Singh M, Mohanty SS, Chakravarty S (2020) Leaf disease detection using support vector machine. In 2020 International conference on communication and signal processing (ICCSP). IEEE, pp 1036\u20131040","DOI":"10.1109\/ICCSP48568.2020.9182128"},{"issue":"18","key":"10944_CR47","doi-asserted-by":"publisher","first-page":"11312","DOI":"10.3390\/su141811312","volume":"14","author":"RG Dawod","year":"2022","unstructured":"Dawod RG, Dobre C (2022) Automatic segmentation and classification system for foliar diseases in sunflower. Sustainability 14(18):11312","journal-title":"Sustainability"},{"issue":"10","key":"10944_CR48","doi-asserted-by":"publisher","first-page":"1745","DOI":"10.3390\/agriculture12101745","volume":"12","author":"M Dhanaraju","year":"2022","unstructured":"Dhanaraju M, Chenniappan P, Ramalingam K, Pazhanivelan S, Kaliaperumal R (2022) Smart farming: internet of things (IoT)-based sustainable agriculture. Agriculture 12(10):1745","journal-title":"Agriculture"},{"key":"10944_CR49","doi-asserted-by":"publisher","first-page":"100108","DOI":"10.1016\/j.atech.2022.100108","volume":"3","author":"LG Divyanth","year":"2023","unstructured":"Divyanth LG, Ahmad A, Saraswat D (2023) A two-stage deep-learning based segmentation model for crop disease quantification based on corn field imagery. Smart Agric Technol 3:100108","journal-title":"Smart Agric Technol"},{"issue":"8","key":"10944_CR50","doi-asserted-by":"publisher","first-page":"22639","DOI":"10.1007\/s11042-023-16247-3","volume":"83","author":"RK Dubey","year":"2024","unstructured":"Dubey RK, Choubey DK (2024) An efficient adaptive feature selection with deep learning model-based paddy plant leaf disease classification. Multimedia Tools Appl 83(8):22639\u201322661","journal-title":"Multimedia Tools Appl"},{"issue":"3","key":"10944_CR51","first-page":"3810","volume":"15","author":"P Enkvetchakul","year":"2021","unstructured":"Enkvetchakul P, Surinta O (2021) Effective data augmentation and training techniques for improving deep learning in plant leaf disease recognition. Appl Sci Eng Progress 15(3):3810","journal-title":"Appl Sci Eng Progress"},{"key":"10944_CR52","doi-asserted-by":"publisher","first-page":"105162","DOI":"10.1016\/j.compag.2019.105162","volume":"169","author":"JG Esgario","year":"2020","unstructured":"Esgario JG, Krohling RA, Ventura JA (2020) Deep learning for classification and severity estimation of coffee leaf biotic stress. Comput Electron Agric 169:105162","journal-title":"Comput Electron Agric"},{"issue":"10","key":"10944_CR53","doi-asserted-by":"publisher","first-page":"2395","DOI":"10.3390\/agronomy12102395","volume":"12","author":"J Eunice","year":"2022","unstructured":"Eunice J, Popescu DE, Chowdary MK, Hemanth J (2022) Deep learning-based leaf disease detection in crops using images for agricultural applications. Agronomy 12(10):2395","journal-title":"Agronomy"},{"key":"10944_CR54","doi-asserted-by":"crossref","unstructured":"Fan H, Xiong B, Mangalam K, Li Y, Yan Z, Malik J, Feichtenhofer C (2021) Multiscale vision transformers. In: Proceedings of the IEEE\/CVF international conference on computer vision. pp 6824\u20136835","DOI":"10.1109\/ICCV48922.2021.00675"},{"key":"10944_CR55","doi-asserted-by":"crossref","unstructured":"Fernandes R, Pessoa A, Nogueira J, Paiva A, Pa\u00e7al I, Salgado M, Cunha A (2024a) Evaluation of deep learning models in search by example using capsule endoscopy images. Procedia Comput Sci 239:2065\u20132073","DOI":"10.1016\/j.procs.2024.06.393"},{"key":"10944_CR56","doi-asserted-by":"crossref","unstructured":"Fernandes R, Pessoa A, Salgado M, De Paiva A, Pacal I, Cunha A (2024b) Enhancing image annotation with object tracking and image retrieval. A systematic review. IEEE Access","DOI":"10.1109\/ACCESS.2024.3406018"},{"key":"10944_CR57","doi-asserted-by":"crossref","unstructured":"G O, Billa SR, Malik V, Bharath E, Sharma S (2024) Grapevine fruits disease detection using different deep learning models. Multimedia Tools Appl, 1\u201326","DOI":"10.1007\/s11042-024-19036-8"},{"key":"10944_CR58","doi-asserted-by":"crossref","unstructured":"Gangadharan K, Kumari GRN, Dhanasekaran D, Malathi K (2020) Automatic detection of plant disease and insect attack using effta algorithm. Int J Adv Comput Sci Appl, 11(2)","DOI":"10.14569\/IJACSA.2020.0110221"},{"issue":"4","key":"10944_CR59","doi-asserted-by":"publisher","first-page":"10989","DOI":"10.1007\/s11042-023-16012-6","volume":"83","author":"V Gautam","year":"2024","unstructured":"Gautam V, Ranjan RK, Dahiya P, Kumar A (2024) ESDNN: a novel ensembled stack deep neural network for mango leaf disease classification and detection. Multimedia Tools Appl 83(4):10989\u201311015","journal-title":"Multimedia Tools Appl"},{"key":"10944_CR60","doi-asserted-by":"crossref","unstructured":"Gayathri S, Wise DJW, Shamini PB, Muthukumaran N (2020) Image analysis and detection of tea leaf disease using deep learning. In: 2020 International conference on electronics and sustainable communication systems (ICESC). IEEE, pp 398\u2013403","DOI":"10.1109\/ICESC48915.2020.9155850"},{"issue":"6","key":"10944_CR61","doi-asserted-by":"publisher","first-page":"489","DOI":"10.3390\/machines10060489","volume":"10","author":"Y Ge","year":"2022","unstructured":"Ge Y, Lin S, Zhang Y, Li Z, Cheng H, Dong J, Shao S, Zhang J, Qi X, Wu Z (2022) Tracking and counting of Tomato at different growth period using an improving YOLO-Deepsort Network for Inspection Robot. Machines 10(6):489","journal-title":"Machines"},{"key":"10944_CR62","doi-asserted-by":"publisher","first-page":"100089","DOI":"10.1016\/j.atech.2022.100089","volume":"3","author":"I Grijalva","year":"2023","unstructured":"Grijalva I, Spiesman BJ, McCornack B (2023) Image classification of sugarcane aphid density using deep convolutional neural networks. Smart Agric Technol 3:100089","journal-title":"Smart Agric Technol"},{"issue":"1","key":"10944_CR63","doi-asserted-by":"publisher","first-page":"129","DOI":"10.28991\/HEF-2022-03-01-09","volume":"3","author":"I Haque","year":"2022","unstructured":"Haque I, Alim M, Alam M, Nawshin S, Noori SRH, Habib MT (2022) Analysis of recognition performance of plant leaf diseases based on machine vision techniques. J Hum Earth Future 3(1):129\u2013137","journal-title":"J Hum Earth Future"},{"issue":"1","key":"10944_CR64","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1016\/j.gltp.2022.03.016","volume":"3","author":"SS Harakannanavar","year":"2022","unstructured":"Harakannanavar SS, Rudagi JM, Puranikmath VI, Siddiqua A, Pramodhini R (2022) Plant leaf disease detection using computer vision and machine learning algorithms. Global Transit Proc 3(1):305\u2013310","journal-title":"Global Transit Proc"},{"key":"10944_CR65","doi-asserted-by":"publisher","first-page":"5390","DOI":"10.1109\/ACCESS.2022.3141371","volume":"10","author":"SM Hassan","year":"2022","unstructured":"Hassan SM, Maji AK (2022) Plant disease identification using a novel convolutional neural network. IEEE Access 10:5390\u20135401","journal-title":"IEEE Access"},{"issue":"12","key":"10944_CR66","doi-asserted-by":"publisher","first-page":"1388","DOI":"10.3390\/electronics10121388","volume":"10","author":"SM Hassan","year":"2021","unstructured":"Hassan SM, Maji AK, Jasi\u0144ski M, Leonowicz Z, Jasi\u0144ska E (2021) Identification of plant-leaf diseases using CNN and transfer-learning approach. Electronics 10(12):1388","journal-title":"Electronics"},{"issue":"2","key":"10944_CR67","doi-asserted-by":"publisher","first-page":"1437","DOI":"10.1007\/s13369-022-06851-0","volume":"48","author":"J He","year":"2023","unstructured":"He J, Liu T, Li L, Hu Y, Zhou G (2023) MFaster r-CNN for maize leaf diseases detection based on machine vision. Arab J Sci Eng 48(2):1437\u20131449","journal-title":"Arab J Sci Eng"},{"key":"10944_CR68","doi-asserted-by":"crossref","unstructured":"Hemalatha A, Vijayakumar J (2021), October Automatic tomato leaf diseases classification and recognition using transfer learning model with image processing techniques. In 2021 Smart Technologies, Communication and Robotics (STCR) (pp. 1\u20135). IEEE","DOI":"10.1109\/STCR51658.2021.9588993"},{"key":"10944_CR69","doi-asserted-by":"publisher","first-page":"106597","DOI":"10.1016\/j.asoc.2020.106597","volume":"96","author":"S Hern\u00e1ndez","year":"2020","unstructured":"Hern\u00e1ndez S, L\u00f3pez JL (2020) Uncertainty quantification for plant disease detection using bayesian deep learning. Appl Soft Comput 96:106597","journal-title":"Appl Soft Comput"},{"key":"10944_CR71","doi-asserted-by":"publisher","first-page":"115287","DOI":"10.1109\/ACCESS.2020.3001237","volume":"8","author":"WJ Hu","year":"2020","unstructured":"Hu WJ, Fan J, Du YX, Li BS, Xiong N, Bekkering E (2020) MDFC\u2013ResNet: an agricultural IoT system to accurately recognize crop diseases. IEEE Access 8:115287\u2013115298","journal-title":"IEEE Access"},{"key":"10944_CR70","doi-asserted-by":"crossref","unstructured":"Hu M, Long S, Wang C, Wang Z (2024) Leaf disease detection using deep convolutional neural networks. J Phys: Conf Ser 2711.1:012020","DOI":"10.1088\/1742-6596\/2711\/1\/012020"},{"key":"10944_CR72","doi-asserted-by":"crossref","unstructured":"Huang Z, Qin A, Lu J, Menon A, Gao J (2020) Grape leaf disease detection and classification using machine learning. In: 2020 international conferences on internet of things (iThings) and IEEE green computing and communications (GreenCom) and IEEE cyber, physical and social computing (CPSCom) and IEEE smart data (SmartData) and IEEE congress on Cybermatics (Cybermatics). IEEE, pp 870\u2013877","DOI":"10.1109\/iThings-GreenCom-CPSCom-SmartData-Cybermatics50389.2020.00150"},{"key":"10944_CR73","unstructured":"Hughes D, Salath\u00e9 M (2015) An open access repository of imageson plant health to enable the development of mobile disease diagnostics.arXiv preprint arXiv: 1511. 08060"},{"key":"10944_CR74","doi-asserted-by":"crossref","unstructured":"Jasim MA, Al-Tuwaijari JM (2020) Plant leaf diseases detection and classification using image processing and deep learning techniques. In: 2020 International conference on computer science and software engineering (CSASE). IEEE, pp 259\u2013265","DOI":"10.1109\/CSASE48920.2020.9142097"},{"key":"10944_CR75","first-page":"150","volume":"3","author":"M Javaid","year":"2022","unstructured":"Javaid M, Haleem A, Singh RP, Suman R (2022) Enhancing smart farming through the applications of agriculture 4.0 technologies. Int J Intell Netw 3:150\u2013164","journal-title":"Int J Intell Netw"},{"key":"10944_CR76","doi-asserted-by":"crossref","unstructured":"Jiang D, Li F, Yang Y, Yu S (2020) A tomato leaf diseases classification method based on deep learning. In 2020 chinese control and decision conference (CCDC). IEEE, pp 1446\u20131450","DOI":"10.1109\/CCDC49329.2020.9164457"},{"key":"10944_CR77","doi-asserted-by":"crossref","unstructured":"Kansal S, Jaiswal A, Sachdeva N (2024) Empirical analysis of deep learning models for tomato leaf disease detection. In: 2024 14th International conference on cloud computing, data science & engineering (confluence). IEEE, pp 430\u2013435","DOI":"10.1109\/Confluence60223.2024.10463386"},{"key":"10944_CR78","doi-asserted-by":"publisher","first-page":"105933","DOI":"10.1016\/j.asoc.2019.105933","volume":"86","author":"R Karthik","year":"2020","unstructured":"Karthik R, Hariharan M, Anand S, Mathikshara P, Johnson A, Menaka R (2020) Attention embedded residual CNN for disease detection in tomato leaves. Appl Soft Comput 86:105933","journal-title":"Appl Soft Comput"},{"issue":"6","key":"10944_CR79","doi-asserted-by":"publisher","first-page":"16019","DOI":"10.1007\/s11042-023-16238-4","volume":"83","author":"P Kaur","year":"2024","unstructured":"Kaur P, Harnal S, Gautam V, Singh MP, Singh SP (2024) Performance analysis of segmentation models to detect leaf diseases in tomato plant. Multimedia Tools Appl 83(6):16019\u201316043","journal-title":"Multimedia Tools Appl"},{"key":"10944_CR80","unstructured":"Kaushik M, Prakash P, Ajay R, Veni S (2020) Tomato leaf disease detection using convolutional neural network with data augmentation. In: 2020 5th International conference on communication and electronics systems (ICCES). IEEE, pp 1125\u20131132"},{"key":"10944_CR81","doi-asserted-by":"publisher","first-page":"75","DOI":"10.59543\/ijmscs.v2i.8343","volume":"2","author":"MM Khalid","year":"2024","unstructured":"Khalid MM, Karan O (2024) Deep learning for plant disease detection. Int J Math Stat Comput Sci 2:75\u201384","journal-title":"Int J Math Stat Comput Sci"},{"issue":"2","key":"10944_CR82","doi-asserted-by":"publisher","first-page":"510","DOI":"10.3390\/agriculture13020510","volume":"13","author":"M Khalid","year":"2023","unstructured":"Khalid M, Sarfraz MS, Iqbal U, Aftab MU, Niedbala G, Rauf HT (2023) Real-time plant health detection using deep convolutional neural networks. Agriculture 13(2):510","journal-title":"Agriculture"},{"key":"10944_CR83","doi-asserted-by":"publisher","first-page":"818","DOI":"10.1007\/s00034-019-01041-0","volume":"39","author":"A Khamparia","year":"2020","unstructured":"Khamparia A, Saini G, Gupta D, Khanna A, Tiwari S, de Albuquerque VHC (2020) Seasonal crops disease prediction and classification using deep convolutional encoder network. Circuits Syst Signal Process 39:818\u2013836","journal-title":"Circuits Syst Signal Process"},{"key":"10944_CR84","doi-asserted-by":"publisher","first-page":"107093","DOI":"10.1016\/j.compag.2022.107093","volume":"198","author":"AI Khan","year":"2022","unstructured":"Khan AI, Quadri SMK, Banday S, Shah JL (2022) Deep diagnosis: a real-time apple leaf disease detection system based on deep learning. Comput Electron Agric 198:107093","journal-title":"Comput Electron Agric"},{"issue":"2","key":"10944_CR85","doi-asserted-by":"publisher","first-page":"4465","DOI":"10.1007\/s11042-023-15809-9","volume":"83","author":"M Khanna","year":"2024","unstructured":"Khanna M, Singh LK, Thawkar S, Goyal M (2024) PlaNet: a robust deep convolutional neural network model for plant leaves disease recognition. Multimedia Tools Appl 83(2):4465\u20134517","journal-title":"Multimedia Tools Appl"},{"key":"10944_CR86","doi-asserted-by":"publisher","first-page":"112942","DOI":"10.1109\/ACCESS.2021.3096895","volume":"9","author":"A Khattak","year":"2021","unstructured":"Khattak A, Asghar MU, Batool U, Asghar MZ, Ullah H, Al-Rakhami M, Gumaei A (2021) Automatic detection of citrus fruit and leaves diseases using deep neural network model. IEEE Access 9:112942\u2013112954","journal-title":"IEEE Access"},{"key":"10944_CR87","doi-asserted-by":"crossref","unstructured":"Kibriya H, Rafique R, Ahmad W, Adnan SM (2021) Tomato leaf disease detection using convolution neural network. In: 2021 International Bhurban conference on applied sciences and technologies (IBCAST). IEEE, pp 346\u2013351","DOI":"10.1109\/IBCAST51254.2021.9393311"},{"issue":"1","key":"10944_CR88","doi-asserted-by":"publisher","first-page":"1404","DOI":"10.1038\/s41598-024-51884-0","volume":"14","author":"AS Kini","year":"2024","unstructured":"Kini AS, Prema KV, Pai SN (2024) Early stage black pepper leaf disease prediction based on transfer learning using ConvNets. Sci Rep 14(1):1404","journal-title":"Sci Rep"},{"key":"10944_CR89","doi-asserted-by":"publisher","first-page":"110425","DOI":"10.1016\/j.measurement.2021.110425","volume":"188","author":"M Koklu","year":"2022","unstructured":"Koklu M, Unlersen MF, Ozkan IA, Aslan MF, Sabanci K (2022) A CNN-SVM study based on selected deep features for grapevine leaves classification. Measurement 188:110425","journal-title":"Measurement"},{"issue":"20","key":"10944_CR90","doi-asserted-by":"publisher","first-page":"10278","DOI":"10.3390\/app122010278","volume":"12","author":"A Ksibi","year":"2022","unstructured":"Ksibi A, Ayadi M, Soufiene BO, Jamjoom MM, Ullah Z (2022) MobiRes-net: a hybrid deep learning model for detecting and classifying olive leaf diseases. Appl Sci 12(20):10278","journal-title":"Appl Sci"},{"key":"10944_CR91","doi-asserted-by":"crossref","unstructured":"Kulkarni S, Keerthi NC, Sunil CK, Pal S, Dash S, Shenoy PD, Venugopal KR (2023) Coffee plant disease identification using enhanced short learning efficientNetV2. In: 2023 IEEE 20th India council international conference (INDICON). IEEE, pp 91\u201396","DOI":"10.1109\/INDICON59947.2023.10440883"},{"key":"10944_CR92","doi-asserted-by":"publisher","first-page":"100311","DOI":"10.1016\/j.atech.2023.100311","volume":"5","author":"P Kumar","year":"2023","unstructured":"Kumar P, Kumar N (2023) Drone-based apple detection: finding the depth of apples using YOLOv7 architecture with multi-head attention mechanism. Smart Agric Technol 5:100311","journal-title":"Smart Agric Technol"},{"key":"10944_CR95","doi-asserted-by":"crossref","unstructured":"Kunduracioglu I, Pacal I (2024) Advancements in deep learning for accurate classification of grape leaves and diagnosis of grape diseases. J Plant Dis Protect","DOI":"10.21203\/rs.3.rs-3146722\/v1"},{"issue":"1","key":"10944_CR93","doi-asserted-by":"publisher","first-page":"28","DOI":"10.31681\/jetol.372826","volume":"1","author":"\u0130 Kundurac\u0131o\u011flu","year":"2018","unstructured":"Kundurac\u0131o\u011flu \u0130 (2018) Examining the interface of lego mindstorms ev3 robot programming. J Educ Technol Online Learn 1(1):28\u201346","journal-title":"J Educ Technol Online Learn"},{"key":"10944_CR94","unstructured":"Kundurac\u0131o\u011flu \u0130, Durak G (2018) A content analysis on gamification. Eur J Open Educ E-Learn Stud"},{"key":"10944_CR96","first-page":"77","volume":"6","author":"M Lachgar","year":"2022","unstructured":"Lachgar M, Hrimech H, Kartit A (2022) Optimization techniques in deep convolutional neuronal networks applied to olive diseases classification. Artif Intell Agric 6:77\u201389","journal-title":"Artif Intell Agric"},{"key":"10944_CR97","doi-asserted-by":"crossref","unstructured":"Lakshmanarao A, Babu MR, Kiran TSR (2021) Plant disease prediction and classification using deep learning ConvNets. In: 2021 International conference on artificial intelligence and machine vision (AIMV). IEEE, pp 1\u20136","DOI":"10.1109\/AIMV53313.2021.9670918"},{"key":"10944_CR98","doi-asserted-by":"crossref","unstructured":"Latha RS, Sreekanth GR, Suganthe RC, Rajadevi R, Karthikeyan S, Kanivel S, Inbaraj B (2021) Automatic detection of tea leaf diseases using deep convolution neural network. In: 2021 International conference on computer communication and informatics (ICCCI).\u00a0IEEE, pp 1\u20136","DOI":"10.1109\/ICCCI50826.2021.9402225"},{"issue":"17","key":"10944_CR99","doi-asserted-by":"publisher","first-page":"2230","DOI":"10.3390\/plants11172230","volume":"11","author":"G Latif","year":"2022","unstructured":"Latif G, Abdelhamid SE, Mallouhy RE, Alghazo J, Kazimi ZA (2022) Deep learning utilization in agriculture: detection of rice plant diseases using an improved CNN model. Plants 11(17):2230","journal-title":"Plants"},{"key":"10944_CR100","doi-asserted-by":"crossref","unstructured":"LeCun Y, Bengio Y, Hinton G (2015) Deep learning. Nature, 521(7553):436\u2013444. Hinton, 2006","DOI":"10.1038\/nature14539"},{"key":"10944_CR202","unstructured":"Lei Ba J, Kiros JR, Hinton GE (2016) Layer normalization. ArXiv e-prints, arXiv-1607."},{"issue":"2","key":"10944_CR102","doi-asserted-by":"publisher","first-page":"95","DOI":"10.3390\/info11020095","volume":"11","author":"K Li","year":"2020","unstructured":"Li K, Lin J, Liu J, Zhao Y (2020) Using deep learning for image-based different degrees of ginkgo leaf disease classification. Information 11(2):95","journal-title":"Information"},{"issue":"3","key":"10944_CR101","doi-asserted-by":"publisher","first-page":"402","DOI":"10.3390\/agriculture12030402","volume":"12","author":"J Li","year":"2022","unstructured":"Li J, Wu J, Lin J, Li C, Lu H, Lin C (2022) Nondestructive identification of litchi downy blight at different stages based on spectroscopy analysis. Agriculture 12(3):402","journal-title":"Agriculture"},{"key":"10944_CR104","first-page":"521544","volume":"11","author":"J Liu","year":"2020","unstructured":"Liu J, Wang X (2020) Tomato diseases and pests detection based on improved Yolo V3 convolutional neural network. Front Plant Sci 11:521544","journal-title":"Front Plant Sci"},{"key":"10944_CR103","doi-asserted-by":"publisher","first-page":"102188","DOI":"10.1109\/ACCESS.2020.2998839","volume":"8","author":"B Liu","year":"2020","unstructured":"Liu B, Tan C, Li S, He J, Wang H (2020) A data augmentation method based on generative adversarial networks for grape leaf disease identification. IEEE Access 8:102188\u2013102198","journal-title":"IEEE Access"},{"key":"10944_CR106","doi-asserted-by":"crossref","unstructured":"Liu Z, Lin Y, Cao Y, Hu H, Wei Y, Zhang Z, Lin S, Guo B (2021) Swin transformer: Hierarchical vision transformer using shifted windows. In Proceedings of the IEEE\/CVF international conference on computer vision. pp 10012\u201310022","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"10944_CR105","doi-asserted-by":"crossref","unstructured":"Liu S, Bai H, Li F, Wang D, Zheng Y, Jiang Q, Sun F (2023) An apple leaf disease identification model for safeguarding apple food safety. Food Sci Technol, 43:e104322","DOI":"10.1590\/fst.104322"},{"issue":"2","key":"10944_CR107","first-page":"41","volume":"11","author":"M Loey","year":"2020","unstructured":"Loey M, ElSawy A, Afify M (2020) Deep learning in plant diseases detection for agricultural crops: a survey. Int J Serv Sci Manag Eng Technol (IJSSMET) 11(2):41\u201358","journal-title":"Int J Serv Sci Manag Eng Technol (IJSSMET)"},{"key":"10944_CR108","doi-asserted-by":"crossref","unstructured":"Mahmood MA, Alsalem K, Computers (2024) Mater Continua, 78(3)","DOI":"10.32604\/cmc.2024.047604"},{"issue":"2","key":"10944_CR109","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1080\/10807039.2022.2064814","volume":"29","author":"R Mahum","year":"2023","unstructured":"Mahum R, Munir H, Mughal ZUN, Awais M, Sher Khan F, Saqlain M, Mahamad S, Tlili I (2023) A novel framework for potato leaf disease detection using an efficient deep learning model. Hum Ecol Risk Assessment: Int J 29(2):303\u2013326","journal-title":"Hum Ecol Risk Assessment: Int J"},{"issue":"23","key":"10944_CR110","doi-asserted-by":"publisher","first-page":"7903","DOI":"10.3390\/s21237903","volume":"21","author":"MH Maqsood","year":"2021","unstructured":"Maqsood MH, Mumtaz R, Haq IU, Shafi U, Zaidi SMH, Hafeez M (2021) Super resolution generative adversarial network (Srgans) for wheat stripe rust classification. Sensors 21(23):7903","journal-title":"Sensors"},{"key":"10944_CR111","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s13593-014-0246-1","volume":"35","author":"F Martinelli","year":"2015","unstructured":"Martinelli F, Scalenghe R, Davino S, Panno S, Scuderi G, Ruisi P, Villa P, Stroppiana D, Boschetti M, Goultar LR, Davis CE, Dandekar AM (2015) Advanced methods of plant disease detection. A review. Agron Sustain Dev 35:1\u201325","journal-title":"Agron Sustain Dev"},{"key":"10944_CR112","unstructured":"Mehta S, Rastegari M (2021) Mobilevit: light-weight, general-purpose, and mobile-friendly vision transformer. arXiv Preprint arXiv :211002178"},{"key":"10944_CR113","doi-asserted-by":"publisher","first-page":"106533","DOI":"10.1016\/j.compag.2021.106533","volume":"191","author":"H Mirhaji","year":"2021","unstructured":"Mirhaji H, Soleymani M, Asakereh A, Abdanan Mehdizadeh S (2021) Fruit detection and load estimation of an orange orchard using the YOLO models through simple approaches in different imaging and illumination conditions. Comput Electron Agric 191:106533","journal-title":"Comput Electron Agric"},{"issue":"4","key":"10944_CR114","doi-asserted-by":"publisher","first-page":"238","DOI":"10.1094\/PHP-05-20-0038-RS","volume":"21","author":"DS Mueller","year":"2020","unstructured":"Mueller DS, Wise KA, Sisson AJ, Allen TW, Bergstrom GC, Bissonnette KM, Wiebold WJ (2020) Corn yield loss estimates due to diseases in the United States and Ontario, Canada, from 2016 to 2019. Plant Health Progress 21(4):238\u2013247","journal-title":"Plant Health Progress"},{"issue":"8","key":"10944_CR115","doi-asserted-by":"publisher","first-page":"12065","DOI":"10.1007\/s11042-022-13737-8","volume":"82","author":"H Mustafa","year":"2023","unstructured":"Mustafa H, Umer M, Hafeez U, Hameed A, Sohaib A, Ullah S, Madni HA (2023) Pepper bell leaf disease detection and classification using optimized convolutional neural network. Multimedia Tools Appl 82(8):12065\u201312080","journal-title":"Multimedia Tools Appl"},{"key":"10944_CR116","doi-asserted-by":"crossref","unstructured":"Nain S, Mittal N, Hanmandlu M (2024) CNN-based plant disease recognition using colour space models. Int J Image Data Fusion, 1\u201314","DOI":"10.1080\/19479832.2023.2300335"},{"issue":"1","key":"10944_CR117","first-page":"509","volume":"13","author":"MH Najim","year":"2024","unstructured":"Najim MH, Abdulateef SK, Alasadi AH (2024) Early detection of tomato leaf diseases based on deep learning techniques. Int J Artif Intell 13(1):509\u2013515","journal-title":"Int J Artif Intell"},{"key":"10944_CR118","doi-asserted-by":"publisher","first-page":"121481","DOI":"10.1016\/j.eswa.2023.121481","volume":"237","author":"M Nawaz","year":"2024","unstructured":"Nawaz M, Nazir T, Javed A, Amin ST, Jeribi F, Tahir A (2024) CoffeeNet: a deep learning approach for coffee plant leaves diseases recognition. Expert Syst Appl 237:121481","journal-title":"Expert Syst Appl"},{"issue":"4","key":"10944_CR119","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1016\/j.cropro.2003.10.001","volume":"23","author":"EC Oerke","year":"2004","unstructured":"Oerke EC, Dehne HW (2004) Safeguarding production\u2014losses in major crops and the role of crop protection. Crop Prot 23(4):275\u2013285","journal-title":"Crop Prot"},{"key":"10944_CR120","doi-asserted-by":"publisher","first-page":"122099","DOI":"10.1016\/j.eswa.2023.122099","volume":"238","author":"I Pacal","year":"2024","unstructured":"Pacal I (2024) Enhancing crop productivity and sustainability through disease identification in maize leaves: exploiting a large dataset with an advanced vision transformer model. Expert Syst Appl 238:122099","journal-title":"Expert Syst Appl"},{"key":"10944_CR122","unstructured":"Pacal I, Kunduracioglu I (2024b) Advanced deep learning approach for early detection of potato leaf diseases using efficient channel attention mechanism. In: International symposium on architecture, engineering and design (ISAED). pp 76\u201386"},{"issue":"1","key":"10944_CR121","doi-asserted-by":"publisher","first-page":"258","DOI":"10.31181\/jscda21202446","volume":"2","author":"\u0130 Pa\u00e7al","year":"2024","unstructured":"Pa\u00e7al \u0130, Kundurac\u0131o\u011flu \u0130 (2024a) Data-efficient vision transformer models for robust classification of sugarcane. J Soft Comput Decis Anal 2(1):258\u2013271","journal-title":"J Soft Comput Decis Anal"},{"key":"10944_CR123","doi-asserted-by":"crossref","unstructured":"Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, Moher D (2021) The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Bmj, 372","DOI":"10.1136\/bmj.n71"},{"issue":"19","key":"10944_CR124","doi-asserted-by":"publisher","first-page":"6540","DOI":"10.3390\/s21196540","volume":"21","author":"Q Pan","year":"2021","unstructured":"Pan Q, Gao M, Wu P, Yan J, Li S (2021) A deep-learning-based approach for wheat yellow rust disease recognition from unmanned aerial vehicle images. Sensors 21(19):6540","journal-title":"Sensors"},{"issue":"4","key":"10944_CR125","doi-asserted-by":"publisher","first-page":"1094","DOI":"10.1016\/S2095-3119(21)63707-3","volume":"21","author":"SQ Pan","year":"2022","unstructured":"Pan SQ, Qiao JF, Rui WANG, Yu HL, Cheng WANG, Taylor K, Pan HY (2022) Intelligent diagnosis of northern corn leaf blight with deep learning model. J Integr Agric 21(4):1094\u20131105","journal-title":"J Integr Agric"},{"key":"10944_CR126","doi-asserted-by":"crossref","unstructured":"Panchal AV, Patel SC, Bagyalakshmi K, Kumar P, Khan IR, Soni M (2023) Image-based plant diseases detection using deep learning. Mater Today: Proc, 80:3500\u20133506","DOI":"10.1016\/j.matpr.2021.07.281"},{"issue":"14","key":"10944_CR127","doi-asserted-by":"publisher","first-page":"6982","DOI":"10.3390\/app12146982","volume":"12","author":"JA Pandian","year":"2022","unstructured":"Pandian JA, Kumar VD, Geman O, Hnatiuc M, Arif M, Kanchanadevi K (2022) Plant disease detection using deep convolutional neural network. Appl Sci 12(14):6982","journal-title":"Appl Sci"},{"key":"10944_CR128","doi-asserted-by":"publisher","first-page":"189960","DOI":"10.1109\/ACCESS.2020.3031914","volume":"8","author":"TN Pham","year":"2020","unstructured":"Pham TN, Van Tran L, Dao SVT (2020) Early disease classification of mango leaves using feed-forward neural network and hybrid metaheuristic feature selection. IEEE Access 8:189960\u2013189973","journal-title":"IEEE Access"},{"key":"10944_CR129","doi-asserted-by":"crossref","unstructured":"Pooniya V, Zhiipao RR, Biswakarma N, Kumar D, Shivay YS, Babu S, Das K, Choudhary AK, Swarnalakshmi K, Jat RD, Choudhary RL, Ram H, Khokhar MK, Mukri G, Lakhena KK, Puniya MM, Jat R, Muralikrishnan L, Singh AK, Lama A (2022) Conservation agriculture based integrated crop management sustains productivity and economic profitability along with soil properties of the maize-wheat rotation. Sci Rep. 12(1):1962","DOI":"10.1038\/s41598-022-05962-w"},{"key":"10944_CR130","doi-asserted-by":"crossref","unstructured":"Qi H, Liang Y, Ding Q, Zou J (2021) Automatic identification of peanut-leaf diseases based on stack ensemble. Appl Sci 11(4):1950","DOI":"10.3390\/app11041950"},{"issue":"7","key":"10944_CR131","doi-asserted-by":"publisher","first-page":"19415","DOI":"10.1007\/s11042-023-16398-3","volume":"83","author":"CK Rai","year":"2024","unstructured":"Rai CK, Pahuja R (2024) Northern maize leaf blight disease detection and segmentation using deep convolution neural networks. Multimedia Tools Appl 83(7):19415\u201319432","journal-title":"Multimedia Tools Appl"},{"issue":"3","key":"10944_CR132","doi-asserted-by":"publisher","first-page":"1681","DOI":"10.11591\/ijeecs.v23.i3.pp1681-1688","volume":"23","author":"A Rajbongshi","year":"2021","unstructured":"Rajbongshi A, Khan T, Pramanik MMRA, Tanvir SM, Siddiquee NRC (2021) Recognition of mango leaf disease using convolutional neural network models: a transfer learning approach. Indonesian J Electr Eng Comput Sci 23(3):1681\u20131688","journal-title":"Indonesian J Electr Eng Comput Sci"},{"key":"10944_CR133","unstructured":"Ramachandran P, Parmar N, Vaswani A, Bello I, Levskaya A, Shlens J (2019) Stand-alone self-attention in vision models. Adv Neural Inf Process Syst, 32"},{"issue":"2","key":"10944_CR134","first-page":"249","volume":"7","author":"S Ramesh","year":"2020","unstructured":"Ramesh S, Vydeki D (2020) Recognition and classification of paddy leaf diseases using optimized deep neural network with Jaya algorithm. Inform Process Agric 7(2):249\u2013260","journal-title":"Inform Process Agric"},{"issue":"2","key":"10944_CR135","doi-asserted-by":"publisher","first-page":"535","DOI":"10.1016\/j.gltp.2021.08.002","volume":"2","author":"US Rao","year":"2021","unstructured":"Rao US, Swathi R, Sanjana V, Arpitha L, Chandrasekhar K, Naik PK (2021) Deep learning precision farming: grapes and mango leaf disease detection by transfer learning. Global Transit Proc 2(2):535\u2013544","journal-title":"Global Transit Proc"},{"issue":"1","key":"10944_CR136","doi-asserted-by":"publisher","first-page":"127","DOI":"10.3390\/agronomy12010127","volume":"12","author":"A Rehman","year":"2022","unstructured":"Rehman A, Saba T, Kashif M, Fati SM, Bahaj SA, Chaudhry H (2022) A revisit of internet of things technologies for monitoring and control strategies in smart agriculture. Agronomy 12(1):127","journal-title":"Agronomy"},{"key":"10944_CR137","doi-asserted-by":"publisher","first-page":"109790","DOI":"10.1016\/j.microc.2023.109790","volume":"197","author":"HC Reis","year":"2024","unstructured":"Reis HC, Turk V (2024) Integrated deep learning and ensemble learning model for deep feature-based wheat disease detection. Microchem J 197:109790","journal-title":"Microchem J"},{"issue":"3","key":"10944_CR138","doi-asserted-by":"publisher","first-page":"413","DOI":"10.3390\/ai2030026","volume":"2","author":"AM Roy","year":"2021","unstructured":"Roy AM, Bhaduri J (2021) A deep learning enabled multi-class plant disease detection model based on computer vision. Ai 2(3):413\u2013428","journal-title":"Ai"},{"issue":"10","key":"10944_CR140","doi-asserted-by":"publisher","first-page":"1319","DOI":"10.3390\/plants9101319","volume":"9","author":"MH Saleem","year":"2020","unstructured":"Saleem MH, Potgieter J, Arif KM (2020) Plant disease classification: a comparative evaluation of convolutional neural networks and deep learning optimizers. Plants 9(10):1319","journal-title":"Plants"},{"issue":"11","key":"10944_CR139","doi-asserted-by":"publisher","first-page":"1451","DOI":"10.3390\/plants9111451","volume":"9","author":"MH Saleem","year":"2020","unstructured":"Saleem MH, Khanchi S, Potgieter J, Arif KM (2020a) Image-based plant disease identification by deep learning meta-architectures. Plants 9(11):1451","journal-title":"Plants"},{"issue":"1","key":"10944_CR141","first-page":"27","volume":"22","author":"GAOGD Sambasivam","year":"2021","unstructured":"Sambasivam GAOGD, Opiyo GD (2021) A predictive machine learning application in agriculture: Cassava disease detection and classification with imbalanced dataset using convolutional neural networks. Egypt Inf J 22(1):27\u201334","journal-title":"Egypt Inf J"},{"key":"10944_CR142","doi-asserted-by":"publisher","first-page":"469689","DOI":"10.3389\/fpls.2021.469689","volume":"12","author":"M Schirrmann","year":"2021","unstructured":"Schirrmann M, Landwehr N, Giebel A, Garz A (2021) Early detection of stripe rust in winter wheat using deep residual neural networks. Front Plant Sci 12:469689","journal-title":"Front Plant Sci"},{"key":"10944_CR143","unstructured":"Sharma A, Bijral RK, Manhas J, Sharma V (2022) Mango leaf diseases detection using deep learning. Int J Knowl Based Comput Syst, 10(1)"},{"key":"10944_CR144","doi-asserted-by":"publisher","first-page":"1031748","DOI":"10.3389\/fpls.2022.1031748","volume":"13","author":"M Shoaib","year":"2022","unstructured":"Shoaib M, Shah B, Ullah I, Ali F, Park SH (2022) Deep learning-based segmentation and classification of leaf images for detection of tomato plant disease. Front Plant Sci 13:1031748","journal-title":"Front Plant Sci"},{"key":"10944_CR145","doi-asserted-by":"crossref","unstructured":"Shrestha G, Das M, Dey N (2020) Plant disease detection using CNN. In: 2020 IEEE applied signal processing conference (ASPCON). IEEE, pp 109\u2013113","DOI":"10.1109\/ASPCON49795.2020.9276722"},{"key":"10944_CR146","doi-asserted-by":"crossref","unstructured":"Shruthi U, Nagaveni V, Raghavendra BK (2019) A review on machine learning classification techniques for plant disease detection. In: 2019 5th International conference on advanced computing & communication systems (ICACCS). IEEE, pp 281\u2013284","DOI":"10.1109\/ICACCS.2019.8728415"},{"key":"10944_CR160","first-page":"1","volume":"12","author":"V Shwetha","year":"2024","unstructured":"Shwetha V, Bhagwat A, Laxmi V (2024) LeafSpotNet: a deep learning framework for detecting leaf spot disease in jasmine plants. Artif Intell Agric 12:1\u201318","journal-title":"Artif Intell Agric"},{"issue":"4","key":"10944_CR148","doi-asserted-by":"publisher","first-page":"1","DOI":"10.4018\/IJAEIS.20211001.oa3","volume":"12","author":"GB Singh","year":"2021","unstructured":"Singh GB, Rani R, Sharma N, Kakkar D (2021) Identification of tomato leaf diseases using deep convolutional neural networks. Int J Agric Environ Inform Syst (IJAEIS) 12(4):1\u201322","journal-title":"Int J Agric Environ Inform Syst (IJAEIS)"},{"key":"10944_CR147","first-page":"1","volume":"2022","author":"AK Singh","year":"2022","unstructured":"Singh AK, Sreenivasu SVN, Mahalaxmi USBK, Sharma H, Patil DD, Asenso E (2022b) Hybrid feature-based disease detection in plant leaf using convolutional neural network, bayesian optimized SVM, and random forest classifier. J Food Qual 2022:1\u201316","journal-title":"J Food Qual"},{"issue":"5","key":"10944_CR149","doi-asserted-by":"publisher","first-page":"6051","DOI":"10.1007\/s11042-021-11763-6","volume":"81","author":"RK Singh","year":"2022","unstructured":"Singh RK, Tiwari A, Gupta RK (2022c) Deep transfer modeling for classification of maize plant leaf disease. Multimedia Tools Appl 81(5):6051\u20136067","journal-title":"Multimedia Tools Appl"},{"key":"10944_CR150","unstructured":"Singh S, Gupta I, Gupta S, Koundal D, Aljahdali S, Mahajan S, Pandit AK (2022a) Deep learning based automated detection of diseases from Apple leaf images. Comput Mater Continua, 71(1)"},{"key":"10944_CR151","doi-asserted-by":"crossref","unstructured":"Singla P, Kalavakonda V, Senthil R (2024) Detection of plant leaf diseases using deep convolutional neural network models. Multimedia Tools Appl, 1\u201317","DOI":"10.1007\/s11042-023-18099-3"},{"issue":"1","key":"10944_CR152","first-page":"153","volume":"30","author":"C\u0130 Sofuo\u011flu","year":"2024","unstructured":"Sofuo\u011flu C\u0130, Birant D (2024) Potato plant leaf disease detection using deep learning method. J Agric Sci 30(1):153\u2013165","journal-title":"J Agric Sci"},{"issue":"3","key":"10944_CR153","doi-asserted-by":"publisher","first-page":"2242","DOI":"10.1109\/TII.2020.2979237","volume":"17","author":"J Su","year":"2020","unstructured":"Su J, Yi D, Su B, Mi Z, Liu C, Hu X, Xu X, Guo L, Chen WH (2020) Aerial visual perception in smart farming: field study of wheat yellow rust monitoring. IEEE Trans Ind Inform 17(3):2242\u20132249","journal-title":"IEEE Trans Ind Inform"},{"key":"10944_CR154","doi-asserted-by":"publisher","first-page":"103615","DOI":"10.1016\/j.micpro.2020.103615","volume":"80","author":"R Sujatha","year":"2021","unstructured":"Sujatha R, Chatterjee JM, Jhanjhi NZ, Brohi SN (2021) Performance of deep learning vs machine learning in plant leaf disease detection. Microprocess Microsyst 80:103615","journal-title":"Microprocess Microsyst"},{"key":"10944_CR155","doi-asserted-by":"crossref","unstructured":"Sun X, Wei J (2020) Identification of maize disease based on transfer learning. J Phys: Conf Ser, 1437.1:012080","DOI":"10.1088\/1742-6596\/1437\/1\/012080"},{"key":"10944_CR156","first-page":"789","volume":"10","author":"CK Sunil","year":"2021","unstructured":"Sunil CK, Jaidhar CD, Patil N (2021) Cardamom plant disease detection approach using EfficientNetV2. Ieee Access 10:789\u2013804","journal-title":"Ieee Access"},{"issue":"4","key":"10944_CR157","first-page":"385","volume":"8","author":"CK Sunil","year":"2022","unstructured":"Sunil CK, Jaidhar CD, Patil N (2022) Binary class and multi-class plant disease detection using ensemble deep learning-based approach. Int J Sustain Agric Manag Inform 8(4):385\u2013407","journal-title":"Int J Sustain Agric Manag Inform"},{"key":"10944_CR158","doi-asserted-by":"publisher","first-page":"120381","DOI":"10.1016\/j.eswa.2023.120381","volume":"228","author":"CK Sunil","year":"2023","unstructured":"Sunil CK, Jaidhar CD, Patil N (2023a) Tomato plant disease classification using multilevel feature fusion with adaptive channel spatial and pixel attention mechanism. Expert Syst Appl 228:120381","journal-title":"Expert Syst Appl"},{"issue":"12","key":"10944_CR159","doi-asserted-by":"publisher","first-page":"14955","DOI":"10.1007\/s10462-023-10517-0","volume":"56","author":"CK Sunil","year":"2023","unstructured":"Sunil CK, Jaidhar CD, Patil N (2023b) Systematic study on deep learning-based plant disease detection or classification. Artif Intell Rev 56(12):14955\u201315052","journal-title":"Artif Intell Rev"},{"issue":"1","key":"10944_CR161","doi-asserted-by":"publisher","first-page":"927","DOI":"10.1007\/s10489-021-02452-w","volume":"52","author":"SF Syed-Ab-Rahman","year":"2022","unstructured":"Syed-Ab-Rahman SF, Hesamian MH, Prasad M (2022) Citrus disease detection and classification using end-to-end anchor-based deep learning model. Appl Intell 52(1):927\u2013938","journal-title":"Appl Intell"},{"issue":"3","key":"10944_CR162","doi-asserted-by":"publisher","first-page":"542","DOI":"10.3390\/agriengineering3030035","volume":"3","author":"L Tan","year":"2021","unstructured":"Tan L, Lu J, Jiang H (2021) Tomato leaf diseases classification based on leaf images: a comparison between classical machine learning and deep learning methods. AgriEngineering 3(3):542\u2013558","journal-title":"AgriEngineering"},{"key":"10944_CR163","doi-asserted-by":"publisher","first-page":"107518","DOI":"10.1016\/j.compag.2022.107518","volume":"204","author":"HT Thai","year":"2023","unstructured":"Thai HT, Le KH, Nguyen NLT (2023) FormerLeaf: an efficient vision transformer for Cassava leaf disease detection. Comput Electron Agric 204:107518","journal-title":"Comput Electron Agric"},{"issue":"1","key":"10944_CR164","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1007\/s41348-020-00403-0","volume":"128","author":"R Thangaraj","year":"2021","unstructured":"Thangaraj R, Anandamurugan S, Kaliappan VK (2021) Automated tomato leaf disease classification using transfer learning-based deep convolution neural network. J Plant Dis Prot 128(1):73\u201386","journal-title":"J Plant Dis Prot"},{"key":"10944_CR166","doi-asserted-by":"publisher","first-page":"101289","DOI":"10.1016\/j.ecoinf.2021.101289","volume":"63","author":"V Tiwari","year":"2021","unstructured":"Tiwari V, Joshi RC, Dutta MK (2021) Dense convolutional neural networks based multiclass plant disease detection and classification using leaf images. Ecol Inform 63:101289","journal-title":"Ecol Inform"},{"key":"10944_CR167","unstructured":"Touvron H, Cord M, Douze M, Massa F, Sablayrolles A, J\u00e9gou H (2021) Training data-efficient image transformers & distillation through attention. In: International conference on machine learning. pp 10347\u201310357"},{"issue":"23","key":"10944_CR168","doi-asserted-by":"publisher","first-page":"7987","DOI":"10.3390\/s21237987","volume":"21","author":"NK Trivedi","year":"2021","unstructured":"Trivedi NK, Gautam V, Anand A, Aljahdali HM, Villar SG, Anand D, Goyal N, Kadry S (2021) Early detection and classification of tomato leaf disease using high-performance deep neural network. Sensors 21(23):7987","journal-title":"Sensors"},{"key":"10944_CR169","doi-asserted-by":"crossref","unstructured":"Tu Z, Talebi H, Zhang H, Yang F, Milanfar P, Bovik A, Li Y (2022) Maxvit: Multi-axis vision transformer. In: European conference on computer vision. Springer, Cham,\u00a0pp 459\u2013479","DOI":"10.1007\/978-3-031-20053-3_27"},{"issue":"9","key":"10944_CR170","doi-asserted-by":"publisher","first-page":"4133","DOI":"10.1007\/s00521-020-05235-5","volume":"33","author":"S U\u011fuz","year":"2021","unstructured":"U\u011fuz S, Uysal N (2021) Classification of olive leaf diseases using deep convolutional neural networks. Neural Comput Appl 33(9):4133\u20134149","journal-title":"Neural Comput Appl"},{"key":"10944_CR171","doi-asserted-by":"crossref","unstructured":"Umamaheswari S, Arjun R, Meganathan D (2018) Weed detection in farm crops using parallel image processing. In: 2018 Conference on information and communication technology (CICT). IEEE, pp 1\u20134","DOI":"10.1109\/INFOCOMTECH.2018.8722369"},{"key":"10944_CR173","unstructured":"Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Polosukhin I (2017) Attention is all you need. Adv Neural Inform Process Syst, 30"},{"key":"10944_CR172","doi-asserted-by":"crossref","unstructured":"Vaswani A, Ramachandran P, Srinivas A, Parmar N, Hechtman B, Shlens J (2021) Scaling local self-attention for parameter efficient visual backbones. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. pp. 12894\u201312904","DOI":"10.1109\/CVPR46437.2021.01270"},{"key":"10944_CR174","doi-asserted-by":"crossref","unstructured":"Verma A, Shekhar S, Garg H (2022) Plant disease classification using deep learning framework. In: 2022 International conference on computational intelligence and sustainable engineering solutions (CISES). IEEE, pp. 512\u2013518","DOI":"10.1109\/CISES54857.2022.9844352"},{"key":"10944_CR175","unstructured":"Wajid AH, Saher N, Nawaz SA, Arshad M, Nasir M (2024) Tomato leaf disease detection and classification using convolutional neural network and machine learning. J Comput Biomed Inform"},{"key":"10944_CR176","doi-asserted-by":"publisher","first-page":"98716","DOI":"10.1109\/ACCESS.2020.2997001","volume":"8","author":"Q Wu","year":"2020","unstructured":"Wu Q, Chen Y, Meng J (2020) DCGAN-based data augmentation for tomato leaf disease identification. IEEE Access 8:98716\u201398728","journal-title":"IEEE Access"},{"key":"10944_CR177","doi-asserted-by":"publisher","first-page":"107825","DOI":"10.1016\/j.compag.2023.107825","volume":"209","author":"Z Wu","year":"2023","unstructured":"Wu Z, Xia F, Zhou S, Xu D (2023) A method for identifying grape stems using keypoints. Comput Electron Agric 209:107825","journal-title":"Comput Electron Agric"},{"key":"10944_CR178","doi-asserted-by":"publisher","first-page":"529357","DOI":"10.3389\/fpls.2020.00751","volume":"11","author":"X Xie","year":"2020","unstructured":"Xie X, Ma Y, Liu B (2020) A deep-learning-based real-time detector for grape leaf diseases using improved convolutional neural networks. Front Plant Sci 11:529357","journal-title":"Front Plant Sci"},{"key":"10944_CR179","doi-asserted-by":"publisher","first-page":"105712","DOI":"10.1016\/j.compag.2020.105712","volume":"177","author":"Y Xiong","year":"2020","unstructured":"Xiong Y, Liang L, Wang L, She J, Wu M (2020) Identification of cash crop diseases using automatic image segmentation algorithm and deep learning with expanded dataset. Comput Electron Agric 177:105712","journal-title":"Comput Electron Agric"},{"issue":"5","key":"10944_CR180","doi-asserted-by":"publisher","first-page":"985","DOI":"10.1007\/s11554-022-01239-7","volume":"19","author":"Y Xu","year":"2022","unstructured":"Xu Y, Chen Q, Kong S, Xing L, Wang Q, Cong X, Zhou Y (2022) Real-time object detection method of melon leaf diseases under complex background in greenhouse. J Real-Time Image Proc 19(5):985\u2013995","journal-title":"J Real-Time Image Proc"},{"key":"10944_CR181","doi-asserted-by":"publisher","first-page":"101247","DOI":"10.1016\/j.ecoinf.2021.101247","volume":"61","author":"S Yadav","year":"2021","unstructured":"Yadav S, Sengar N, Singh A, Singh A, Dutta MK (2021) Identification of disease using deep learning and evaluation of bacteriosis in peach leaf. Ecol Inform 61:101247","journal-title":"Ecol Inform"},{"issue":"4","key":"10944_CR182","first-page":"1047","volume":"103","author":"R Yakkundimath","year":"2022","unstructured":"Yakkundimath R, Saunshi G, Anami B, Palaiah S (2022) Classification of rice diseases using convolutional neural network models. J Inst Eng (India): Ser B 103(4):1047\u20131059","journal-title":"J Inst Eng (India): Ser B"},{"issue":"12","key":"10944_CR183","doi-asserted-by":"publisher","first-page":"3535","DOI":"10.3390\/s20123535","volume":"20","author":"Q Yan","year":"2020","unstructured":"Yan Q, Yang B, Wang W, Wang B, Chen P, Zhang J (2020) Apple leaf diseases recognition based on an improved convolutional neural network. Sensors 20(12):3535","journal-title":"Sensors"},{"issue":"9","key":"10944_CR184","doi-asserted-by":"publisher","first-page":"3388","DOI":"10.3390\/s22093388","volume":"22","author":"Q Yao","year":"2022","unstructured":"Yao Q, Zhang H (2022) Improving agricultural product traceability using blockchain. Sensors 22(9):3388","journal-title":"Sensors"},{"key":"10944_CR185","doi-asserted-by":"crossref","unstructured":"Yatoo AA, Sharma A (2021) A novel model for automatic crop disease detection. In: 2021 Sixth international conference on image information processing (ICIIP). IEEE, 6:310\u2013313","DOI":"10.1109\/ICIIP53038.2021.9702553"},{"key":"10944_CR186","doi-asserted-by":"publisher","first-page":"829479","DOI":"10.3389\/fpls.2022.829479","volume":"13","author":"T Zeng","year":"2022","unstructured":"Zeng T, Li C, Zhang B, Wang R, Fu W, Wang J, Zhang X (2022) Rubber leaf disease recognition based on improved deep convolutional neural networks with a cross-scale attention mechanism. Front Plant Sci 13:829479","journal-title":"Front Plant Sci"},{"key":"10944_CR189","doi-asserted-by":"publisher","first-page":"107511","DOI":"10.1016\/j.compag.2022.107511","volume":"204","author":"S Zhang","year":"2023","unstructured":"Zhang S, Zhang C (2023) Modified U-Net for plant diseased leaf image segmentation. Comput Electron Agric 204:107511","journal-title":"Comput Electron Agric"},{"key":"10944_CR188","unstructured":"Zhang D, Yang H, Cao J (2021a) Identify apple leaf diseases using deep learning algorithm. arXiv Preprint arXiv :210712598"},{"issue":"19","key":"10944_CR190","doi-asserted-by":"publisher","first-page":"3892","DOI":"10.3390\/rs13193892","volume":"13","author":"T Zhang","year":"2021","unstructured":"Zhang T, Xu Z, Su J, Yang Z, Liu C, Chen WH, Li J (2021b) Ir-unet: irregular segmentation u-shape network for wheat yellow rust detection by UAV multispectral imagery. Remote Sens 13(19):3892","journal-title":"Remote Sens"},{"issue":"17","key":"10944_CR187","doi-asserted-by":"publisher","first-page":"4150","DOI":"10.3390\/rs14174150","volume":"14","author":"C Zhang","year":"2022","unstructured":"Zhang C, Kang F, Wang Y (2022) An improved apple object detection method based on lightweight YOLOv4 in complex backgrounds. Remote Sens 14(17):4150. https:\/\/doi.org\/10.3390\/rs14174150","journal-title":"Remote Sens"},{"key":"10944_CR192","doi-asserted-by":"publisher","first-page":"107905","DOI":"10.1016\/j.compag.2023.107905","volume":"210","author":"X Zhang","year":"2023","unstructured":"Zhang X, Zhu D, Wen R (2023) SwinT-YOLO: detection of densely distributed maize tassels in remote sensing images. Comput Electron Agric 210:107905","journal-title":"Comput Electron Agric"},{"key":"10944_CR191","doi-asserted-by":"crossref","unstructured":"Zhang X, Li F, Zheng H, Mu W (2024) UPFormer: U-sharped perception lightweight transformer for segmentation of field grape leaf diseases. Expert Syst Appl, 123546","DOI":"10.1016\/j.eswa.2024.123546"},{"key":"10944_CR193","doi-asserted-by":"publisher","first-page":"107087","DOI":"10.1016\/j.compag.2022.107087","volume":"198","author":"J Zhao","year":"2022","unstructured":"Zhao J, Yan J, Xue T, Wang S, Qiu X, Yao X, Tian Y, Zhu Y, Cao W, Zhang X (2022) A deep learning method for oriented and small wheat spike detection (OSWSDet) in UAV images. Comput Electron Agric 198:107087","journal-title":"Comput Electron Agric"},{"key":"10944_CR194","doi-asserted-by":"publisher","first-page":"105146","DOI":"10.1016\/j.compag.2019.105146","volume":"168","author":"Y Zhong","year":"2020","unstructured":"Zhong Y, Zhao M (2020) Research on deep learning in apple leaf disease recognition. Comput Electron Agric 168:105146","journal-title":"Comput Electron Agric"},{"key":"10944_CR195","doi-asserted-by":"crossref","unstructured":"Zia Ur Rehman M, Ahmed F, Attique Khan M, Tariq U, Jamal S, Ahmad SJ, Hussain I (2021) Classification of citrus plant diseases using deep transfer learning. Comput Mater Continua, 70(1)","DOI":"10.32604\/cmc.2022.019046"}],"container-title":["Artificial Intelligence Review"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-024-10944-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10462-024-10944-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-024-10944-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,24]],"date-time":"2024-10-24T02:14:20Z","timestamp":1729736060000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10462-024-10944-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,30]]},"references-count":195,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2024,11]]}},"alternative-id":["10944"],"URL":"https:\/\/doi.org\/10.1007\/s10462-024-10944-7","relation":{},"ISSN":["1573-7462"],"issn-type":[{"value":"1573-7462","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,30]]},"assertion":[{"value":"10 September 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 September 2024","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"304"}}