{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T09:04:38Z","timestamp":1769850278305,"version":"3.49.0"},"publisher-location":"Cham","reference-count":14,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031622168","type":"print"},{"value":"9783031622175","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-62217-5_16","type":"book-chapter","created":{"date-parts":[[2024,6,10]],"date-time":"2024-06-10T02:01:34Z","timestamp":1717984894000},"page":"186-200","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Potato Leaf Disease Classification Using Deep Learning Model"],"prefix":"10.1007","author":[{"given":"Raj","family":"Kumar","sequence":"first","affiliation":[]},{"given":"Tushar","family":"Agrawal","sequence":"additional","affiliation":[]},{"given":"Vinayak Dhar","family":"Dwivedi","sequence":"additional","affiliation":[]},{"given":"Harsh","family":"Khatter","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,6,11]]},"reference":[{"key":"16_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2022\/5421312","volume":"2022","author":"A Verma","year":"2022","unstructured":"Verma, A., et al.: Plantosphere: next generation adaptive and smart agriculture system. J. Sensors 2022, 1\u201310 (2022)","journal-title":"J. Sensors"},{"key":"16_CR2","doi-asserted-by":"publisher","first-page":"14","DOI":"10.5815\/ijigsp.2021.05.02","volume":"13","author":"P Dayang","year":"2021","unstructured":"Dayang, P., Meli, A.S.K.: Evaluation of image segmentation algorithms for plant disease detection. Int. J. Image Graph. Signal Process 13, 14\u201326 (2021)","journal-title":"Int. J. Image Graph. Signal Process"},{"issue":"2","key":"16_CR3","doi-asserted-by":"publisher","first-page":"1258","DOI":"10.1109\/TASE.2020.3041499","volume":"19","author":"QH Cap","year":"2020","unstructured":"Cap, Q.H., Uga, H., Kagiwada, S., Iyatomi, H.: LeafGAN: an effective data augmentation method for practical plant disease diagnosis. IEEE Trans. Autom. Sci. Eng. 19(2), 1258\u20131267 (2020)","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"issue":"2","key":"16_CR4","doi-asserted-by":"publisher","first-page":"294","DOI":"10.3390\/agriengineering3020020","volume":"3","author":"MEH Chowdhury","year":"2021","unstructured":"Chowdhury, M.E.H., et al.: Automatic and reliable leaf disease detection using deep learning techniques. AgriEngineering 3(2), 294\u2013312 (2021)","journal-title":"AgriEngineering"},{"key":"16_CR5","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.: Plant leaf disease classification using EfficientNet deep learning model. Eco. Inform. 61, 101182 (2021)","journal-title":"Eco. Inform."},{"key":"16_CR6","doi-asserted-by":"publisher","first-page":"106723","DOI":"10.1016\/j.knosys.2020.106723","volume":"214","author":"J Gao","year":"2021","unstructured":"Gao, J., Westergaard, J.C., Riis Sundmark, E.H., Bagge, M., Liljeroth, E., Alexandersson, E.: Automatic late blight lesion recognition and severity quantification based on field imagery of diverse potato genotypes by deep learning. Knowl. Based Syst. 214, 106723 (2021)","journal-title":"Knowl. Based Syst."},{"key":"16_CR7","doi-asserted-by":"publisher","first-page":"480","DOI":"10.1016\/j.matpr.2021.05.584","volume":"51","author":"S Ashwinkumar","year":"2022","unstructured":"Ashwinkumar, S., Rajagopal, S., Manimaran, V., Jegajothi, B.: Automated plant leaf disease detection and classification using optimal MobileNet based convolutional neural networks. Mater. Today Proc. 51, 480\u2013487 (2022)","journal-title":"Mater. Today Proc."},{"issue":"6","key":"16_CR8","first-page":"1059","volume":"23","author":"A Bhatia","year":"2020","unstructured":"Bhatia, A., Chug, A., Singh, A.P.: Application of extreme learning machine in plant disease prediction for highly imbalanced dataset. J. Stat. Manage. Syst. 23(6), 1059\u20131068 (2020)","journal-title":"J. Stat. Manage. Syst."},{"issue":"3","key":"16_CR9","doi-asserted-by":"publisher","first-page":"511","DOI":"10.3390\/sym13030511","volume":"13","author":"SM Minhaz Hossain","year":"2021","unstructured":"Minhaz Hossain, S.M., Deb, K., Dhar, P.K., Koshiba, T.: Plant leaf disease recognition using depth-wise separable convolution-based models. Symmetry 13(3), 511 (2021)","journal-title":"Symmetry"},{"key":"16_CR10","doi-asserted-by":"crossref","unstructured":"Kumar, R., Shukla, N., Princee: Plant disease detection and crop recommendation using CNN and machine learning. In: 2022 International Mobile and Embedded Technology Conference (MECON), pp. 168\u2013172. IEEE (2022)","DOI":"10.1109\/MECON53876.2022.9752173"},{"key":"16_CR11","doi-asserted-by":"crossref","unstructured":"Dwivedi, P., Kumar, S., Vijh, S., Chaturvedi, Y.: Study of machine learning techniques for plant disease recognition in agriculture. In: 2021 11th International Conference on Cloud Computing, Data Science & Engineering (Confluence), pp. 752\u2013756. IEEE (2021)","DOI":"10.1109\/Confluence51648.2021.9377186"},{"key":"16_CR12","doi-asserted-by":"crossref","unstructured":"Kiran, S., Kanumalli, S.S., Krishna, K.V.S.S.R., Chandra, N.: WITHDRAWN: internet of things integrated smart agriculture for weather predictions and preventive mechanism. Mater. Today Proc. (2021)","DOI":"10.1016\/j.matpr.2020.11.081"},{"key":"16_CR13","doi-asserted-by":"crossref","unstructured":"Khatter, H., Aggarwal, V., Ahlawat, A.K.: Performance analysis of the competitive learning algorithms on gaussian data in automatic cluster selection. In: 2016 Second International Conference on Computational Intelligence & Communication Technology (CICT), pp. 48\u201353. IEEE (2016)","DOI":"10.1109\/CICT.2016.19"},{"key":"16_CR14","first-page":"1","volume":"2022","author":"S Sharma","year":"2022","unstructured":"Sharma, S., et al.: Deep learning model for automatic classification and prediction of brain tumor. J. Sensors 2022, 1\u201311 (2022)","journal-title":"J. Sensors"}],"container-title":["Communications in Computer and Information Science","Machine Learning, Image Processing, Network Security and Data Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-62217-5_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,10]],"date-time":"2024-06-10T02:04:47Z","timestamp":1717985087000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-62217-5_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031622168","9783031622175"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-62217-5_16","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"value":"1865-0929","type":"print"},{"value":"1865-0937","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"11 June 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MIND","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Machine Learning, Image Processing, Network Security and Data Sciences","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hamirpur","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 December 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 December 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"mind2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/mind2023.nith.ac.in\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}