{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T14:24:54Z","timestamp":1774448694406,"version":"3.50.1"},"reference-count":46,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2021,7,2]],"date-time":"2021-07-02T00:00:00Z","timestamp":1625184000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,7,2]],"date-time":"2021-07-02T00:00:00Z","timestamp":1625184000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Comb Optim"],"published-print":{"date-parts":[[2022,3]]},"DOI":"10.1007\/s10878-021-00770-w","type":"journal-article","created":{"date-parts":[[2021,7,2]],"date-time":"2021-07-02T19:03:17Z","timestamp":1625252597000},"page":"312-349","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Optimized threshold-based convolutional neural network for plant leaf classification: a challenge towards untrained data"],"prefix":"10.1007","volume":"43","author":[{"given":"Bhanuprakash","family":"Dudi","sequence":"first","affiliation":[]},{"given":"V.","family":"Rajesh","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,7,2]]},"reference":[{"issue":"5","key":"770_CR1","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1002\/cplx.21634","volume":"21","author":"O Abedinia","year":"2016","unstructured":"Abedinia O, Amjady N, Ghasemi A (2016) A new metaheuristic algorithm based on shark smell optimization. Complexity 21(5):97\u2013116","journal-title":"Complexity"},{"key":"770_CR2","unstructured":"Bhambere S (2011) The long wait for Health in India-A study of waiting time for patients in a tertiary care hospital in Western India. Int J Basic Appl Res 7(12)"},{"key":"770_CR3","doi-asserted-by":"publisher","first-page":"151754","DOI":"10.1109\/ACCESS.2019.2935515","volume":"7","author":"W Bin","year":"2019","unstructured":"Bin W, Dian W (2019) Plant leaves classification: a few-shot learning method based on siamese network. IEEE Access 7:151754\u2013151763","journal-title":"IEEE Access"},{"key":"770_CR4","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1016\/j.ins.2016.09.023","volume":"374","author":"J Caoa","year":"2016","unstructured":"Caoa J, Wanga B, Brown D (2016) Similarity based leaf image retrieval using multiscale R-angle description. Inf Sci 374:51\u201364","journal-title":"Inf Sci"},{"issue":"2","key":"770_CR5","doi-asserted-by":"crossref","first-page":"883","DOI":"10.1016\/j.amc.2006.07.072","volume":"185","author":"J-X Du","year":"2007","unstructured":"Du J-X, Wang X-F, Zhang G-J (2007) Leaf shape based plant species recognition. Appl Math Comput 185(2):883\u2013893","journal-title":"Appl Math Comput"},{"issue":"10","key":"770_CR6","doi-asserted-by":"publisher","first-page":"2302","DOI":"10.1109\/TKDE.2012.196","volume":"25","author":"X Fang","year":"2013","unstructured":"Fang X (Oct. 2013) Inference-based na\u00efve bayes: turning na\u00efve bayes cost-sensitive. IEEE Trans Knowl Data Eng 25(10):2302\u20132313","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"770_CR7","doi-asserted-by":"publisher","first-page":"196747","DOI":"10.1109\/ACCESS.2020.3034033","volume":"8","author":"AMASM Fati","year":"2020","unstructured":"Fati AMASM (2020) Efficient and automated herbs classification approach based on shape and texture features using deep learning. IEEE Access 8:196747\u2013196764","journal-title":"IEEE Access"},{"issue":"11","key":"770_CR8","doi-asserted-by":"publisher","first-page":"2592","DOI":"10.1109\/TNNLS.2016.2598657","volume":"28","author":"F Fern\u00e1ndez-Navarro","year":"2017","unstructured":"Fern\u00e1ndez-Navarro F, Carbonero-Ruz M, Becerra Alonso D, Torres-Jim\u00e9nez M (2017) Global sensitivity estimates for neural network classifiers. IEEE Trans Neural Netw Learn Syst 28(11):2592\u20132604","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"3","key":"770_CR9","first-page":"663","volume":"16","author":"X Guoqing","year":"2020","unstructured":"Guoqing X, Ran W, Wang Q (2020) Multi-granular angle description for plant leaf classification and retrieval based on quotient space. J Inf Process Syst 16(3):663\u2013676","journal-title":"J Inf Process Syst"},{"key":"770_CR10","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1016\/j.biosystemseng.2015.12.007","volume":"142","author":"K Horaisova","year":"2016","unstructured":"Horaisova K, Kukal J (2016) Leaf classification from binary image via artificial intelligence. Biosyst Eng 142:83\u2013100","journal-title":"Biosyst Eng"},{"issue":"6","key":"770_CR11","doi-asserted-by":"publisher","first-page":"853","DOI":"10.1109\/LSP.2018.2809688","volume":"25","author":"J Hu","year":"2018","unstructured":"Hu J, Chen Z, Yang M, Zhang R, Cui Y (June 2018) A multiscale fusion convolutional neural network for plant leaf recognition. IEEE Signal Process Lett 25(6):853\u2013857","journal-title":"IEEE Signal Process Lett"},{"key":"770_CR12","doi-asserted-by":"crossref","unstructured":"Jen-Tzung C (2019) Chapter 2 - model-based source separation. Source Sep Mach Learn, pp 21\u201352","DOI":"10.1016\/B978-0-12-804566-4.00013-9"},{"key":"770_CR13","unstructured":"Kadir A, Nugroho LE, Susanto A, Santosa PI (2013) Leaf classification using shape, color, and texture features"},{"key":"770_CR14","doi-asserted-by":"publisher","first-page":"102","DOI":"10.1016\/j.cviu.2014.11.001","volume":"133","author":"C Kalyoncu","year":"2015","unstructured":"Kalyoncu C, Toygar \u00d6 (2015) Geometric leaf classification. Comput vis Image Underst 133:102\u2013109","journal-title":"Comput vis Image Underst"},{"issue":"7","key":"770_CR15","doi-asserted-by":"publisher","first-page":"700","DOI":"10.1049\/iet-cvi.2015.0414","volume":"10","author":"C Kalyoncu","year":"2016","unstructured":"Kalyoncu C, Toygar \u00d6 (2016) GTCLC: leaf classification method using multiple descriptors. IET Comput vis 10(7):700\u2013708","journal-title":"IET Comput vis"},{"issue":"3","key":"770_CR16","doi-asserted-by":"publisher","first-page":"581","DOI":"10.1134\/S105466181703018X","volume":"27","author":"HX Kan","year":"2017","unstructured":"Kan HX, Jin L, Zhou FL (2017) Classification of medicinal plant leaf image based on multi-feature extraction. Pattern Recognit Image Anal 27(3):581\u2013587","journal-title":"Pattern Recognit Image Anal"},{"issue":"1","key":"770_CR17","first-page":"17","volume":"37","author":"M Keivani","year":"2020","unstructured":"Keivani M, Mazloum J, Sedaghatfar E (2020) Automated analysis of leaf shape, texture, and color features for plant classification. Int Inf Eng Technol Assoc 37(1):17\u201328","journal-title":"Int Inf Eng Technol Assoc"},{"key":"770_CR18","unstructured":"Kusumawardani W, Muzzazinah, Ramli (2018) Plant leaf classification using multiple descriptors: a hierarchical approach. J King Saud Univ Comput Inf Sci, Available online"},{"key":"770_CR19","doi-asserted-by":"crossref","unstructured":"Liu J, Yang S, Cheng Y, Song Z (2018) Plant leaf classification based on deep learning. In: Chinese automation congress (CAC), pp 3165\u20133169","DOI":"10.1109\/CAC.2018.8623427"},{"issue":"4","key":"770_CR20","doi-asserted-by":"publisher","first-page":"1465","DOI":"10.3233\/IFS-151626","volume":"29","author":"L Longlong","year":"2015","unstructured":"Longlong L, Garibaldi JM, Dongjian H (October 2015) Leaf classication using multiple feature analysis based on semi-supervised clustering. J Intell Fuzzy Syst 29(4):1465\u20131477","journal-title":"J Intell Fuzzy Syst"},{"key":"770_CR21","doi-asserted-by":"crossref","unstructured":"Mallah C, Cope J, Orwell J (2013) Plant leaf classification using probabilistic integration of shape, texture and margin features","DOI":"10.2316\/P.2013.798-098"},{"key":"770_CR22","unstructured":"Marco S, Michael R, David B, Jana W, Patrick M, Image-based classification of plant genus and family for trained and untrained plant species. BMC Bioinform 20(4)"},{"issue":"2","key":"770_CR23","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1002\/ima.22087","volume":"24","author":"M MarsalineBeno","year":"2014","unstructured":"MarsalineBeno M, Valarmathi IR, Swamy SM, Rajakumar BR (2014) Threshold prediction for segmenting tumour from brain MRI scans. Int J Imaging Syst Technol 24(2):129\u2013137","journal-title":"Int J Imaging Syst Technol"},{"key":"770_CR24","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1016\/j.advengsoft.2016.01.008","volume":"95","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili S, Lewis A (2016) The whale optimization algorithm. Adv Eng Softw 95:51\u201367","journal-title":"Adv Eng Softw"},{"issue":"4","key":"770_CR25","doi-asserted-by":"publisher","first-page":"369","DOI":"10.1049\/iet-cvi.2018.5028","volume":"13","author":"F Mostajer Kheirkhah","year":"2019","unstructured":"Mostajer Kheirkhah F, Asghari H (2019) Plant leaf classification using GIST texture features. IET Comput Vis 13(4):369\u2013375","journal-title":"IET Comput Vis"},{"issue":"5","key":"770_CR26","first-page":"447","volume":"11","author":"V Narayan","year":"2014","unstructured":"Narayan V, Subbarayan G (Sep. 2014) An optimal feature subset selection using GA for leaf classication. Int Arab J Inf Technol 11(5):447\u2013451","journal-title":"Int Arab J Inf Technol"},{"issue":"2","key":"770_CR27","doi-asserted-by":"publisher","first-page":"618","DOI":"10.1016\/j.asoc.2009.08.029","volume":"10","author":"MEH Pedersen","year":"2010","unstructured":"Pedersen MEH, Chipperfield AJ (March 2010) Simplifying particle swarm optimization. Appl Soft Comput 10(2):618\u2013628","journal-title":"Appl Soft Comput"},{"key":"770_CR28","doi-asserted-by":"publisher","first-page":"2352","DOI":"10.1162\/neco_a_00990","volume":"29","author":"W Rawat","year":"2017","unstructured":"Rawat W, Wang Z (June 2017) Deep convolutional neural networks for image classification: a comprehensive review. Neural Comput 29:2352\u20132449","journal-title":"Neural Comput"},{"key":"770_CR29","doi-asserted-by":"publisher","first-page":"326","DOI":"10.1016\/j.compag.2017.08.029","volume":"142","author":"MBH Rhouma","year":"2017","unstructured":"Rhouma MBH, \u017duni\u0107 J (2017) Mohammed chachan younis, \u201cmoment invariants for multi-component shapes with applications to leaf classification.\u201d Comput Electron Agric 142:326\u2013337","journal-title":"Comput Electron Agric"},{"key":"770_CR30","doi-asserted-by":"publisher","first-page":"326","DOI":"10.1016\/j.compag.2017.08.029","volume":"142","author":"MBH Rhouma","year":"2017","unstructured":"Rhouma MBH, Z\u0161unic J, Younis MC (Nov. 2017) Moment invariants for multi-component shapes with applications to leaf classication. Comput Electron Agricult 142:326\u2013337","journal-title":"Comput Electron Agricult"},{"key":"770_CR31","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1016\/j.comcom.2020.03.031","volume":"163","author":"A Sai Srinivas","year":"2020","unstructured":"Sai Srinivas A, Manivannan SS (2020) Prevention of hello flood attack in IoT using combination of deep learning with improved rider optimization algorithm. Comput Commun 163:162\u2013175","journal-title":"Comput Commun"},{"key":"770_CR32","doi-asserted-by":"publisher","first-page":"270","DOI":"10.1016\/j.compag.2018.12.038","volume":"157","author":"G Saleem","year":"2019","unstructured":"Saleem G, Akhtar M, Ahmed N, Qureshi WS (February 2019) Automated analysis of visual leaf shape features for plant classification. Comput Electron Agric 157:270\u2013280","journal-title":"Comput Electron Agric"},{"key":"770_CR33","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.advengsoft.2013.12.007","volume":"69","author":"M Seyedali","year":"2014","unstructured":"Seyedali M, Seyed MM, Andrew L (2014) Grey wolf optimizer. Adv Eng Softw 69:46\u201361","journal-title":"Adv Eng Softw"},{"issue":"10","key":"770_CR34","doi-asserted-by":"publisher","first-page":"2677","DOI":"10.1016\/j.ultrasmedbio.2015.05.015","volume":"41","author":"Y Shuang","year":"2015","unstructured":"Shuang Y, Kok KT, Ban LS, Alex TH (2015) Lumbar ultrasound image feature extraction and classification with support vector machine. Ultrasound Med Biol 41(10):2677\u20132689","journal-title":"Ultrasound Med Biol"},{"key":"770_CR35","doi-asserted-by":"publisher","first-page":"43721","DOI":"10.1109\/ACCESS.2019.2907383","volume":"7","author":"UP Singh","year":"2019","unstructured":"Singh UP, Chouhan SS, Jain S, Jain S (2019) Multilayer convolution neural network for the classication of mango leaves infected by anthracnose disease. IEEE Access 7:43721\u201343729","journal-title":"IEEE Access"},{"key":"770_CR36","doi-asserted-by":"crossref","unstructured":"Swamy SM, Rajakumar BR, Valarmathi IR (2013) Design of hybrid wind and photovoltaic power system using opposition-based genetic algorithm with cauchy mutation. IET Chennai fourth international conference on sustainable energy and intelligent systems (SEISCON 2013), Chennai, India, December 2013","DOI":"10.1049\/ic.2013.0361"},{"key":"770_CR37","doi-asserted-by":"publisher","first-page":"1011","DOI":"10.1016\/j.neucom.2015.05.024","volume":"168","author":"Z Tang","year":"2015","unstructured":"Tang Z, Su Y, Er MJ et al (2015) A local binary pattern based texture descriptors for classification of tea leaves. Neurocomputing 168:1011\u20131023","journal-title":"Neurocomputing"},{"key":"770_CR38","doi-asserted-by":"crossref","unstructured":"Tavakoli H, Alirezazadeh P, Hedayatipour A, BanijamaliNasib AH, Landwehr N (2021) Leaf image-based classification of some common bean cultivars using discriminative convolutional neural networks. In: Computers and electronics in agriculture, vol 181","DOI":"10.1016\/j.compag.2020.105935"},{"key":"770_CR39","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1007\/978-3-642-54924-3_13","volume":"277","author":"HS Wu","year":"2014","unstructured":"Wu HS, Pu PT (2014) He GQ (2014) Leaf recognition based on BGP texture matching. Foundat Intell Syst Adv Intell Syst Comput 277:135\u2013142","journal-title":"Foundat Intell Syst Adv Intell Syst Comput"},{"issue":"12","key":"770_CR40","doi-asserted-by":"publisher","first-page":"2328","DOI":"10.1049\/iet-ipr.2018.6551","volume":"13","author":"G Xu","year":"2019","unstructured":"Xu G, Li C, Wang Q (2019) Unified multi-scale method for fast leaf classification and retrieval using geometric information. IET Image Process 13(12):2328\u20132334","journal-title":"IET Image Process"},{"key":"770_CR41","doi-asserted-by":"publisher","first-page":"38","DOI":"10.4028\/www.scientific.net\/KEM.464.38","volume":"464","author":"P Ye","year":"2011","unstructured":"Ye P, Weng GR (2011) Classification and recognition of plant leaf based on neural networks. Key Eng Mater 464:38\u201342","journal-title":"Key Eng Mater"},{"key":"770_CR42","doi-asserted-by":"crossref","unstructured":"Yeganeh H, Ziaei A, Rezaie A (2008) A novel approach for contrast enhancement based on histogram equalization. In: Proceedings of the international conference on computer and communication engineering 2008 May 13\u201315, Kuala Lumpur, Malaysia","DOI":"10.1109\/ICCCE.2008.4580607"},{"key":"770_CR43","doi-asserted-by":"publisher","first-page":"1891","DOI":"10.1016\/j.patcog.2013.01.015","volume":"46","author":"S Zhang","year":"2013","unstructured":"Zhang S, Lei Y, Dong T, Zhang X-P (2013) Label propagation based supervised locality projection analysis for plant leaf classification. Pattern Recogn 46:1891\u20131897","journal-title":"Pattern Recogn"},{"issue":"4","key":"770_CR44","doi-asserted-by":"publisher","first-page":"953","DOI":"10.1007\/s10044-015-0488-9","volume":"19","author":"S Zhang","year":"2015","unstructured":"Zhang S, Lei Y, Zhang C, Yihua Hu (2015) Semi-supervised orthogonal discriminant projection for plant leaf classification. Pattern Anal Appl 19(4):953\u2013961","journal-title":"Pattern Anal Appl"},{"key":"770_CR45","doi-asserted-by":"publisher","first-page":"953","DOI":"10.1007\/s10044-015-0488-9","volume":"19","author":"S Zhang","year":"2016","unstructured":"Zhang S, Lei Y, Zhang C et al (2016) Semi-supervised orthogonal discriminant projection for plant leaf classification. Pattern Anal Appl 19:953\u2013961","journal-title":"Pattern Anal Appl"},{"key":"770_CR46","unstructured":"Zhu Y, Huang C (2011) An improved median filtering algorithm combined with average filtering. In: 2011 third international conference on measuring technology and mechatronics automation, China, 2011"}],"container-title":["Journal of Combinatorial Optimization"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10878-021-00770-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10878-021-00770-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10878-021-00770-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,5]],"date-time":"2023-11-05T15:54:46Z","timestamp":1699199686000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10878-021-00770-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,2]]},"references-count":46,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2022,3]]}},"alternative-id":["770"],"URL":"https:\/\/doi.org\/10.1007\/s10878-021-00770-w","relation":{},"ISSN":["1382-6905","1573-2886"],"issn-type":[{"value":"1382-6905","type":"print"},{"value":"1573-2886","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,2]]},"assertion":[{"value":"9 June 2021","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 July 2021","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}