{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T16:25:19Z","timestamp":1776183919360,"version":"3.50.1"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783031116322","type":"print"},{"value":"9783031116339","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"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":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-11633-9_6","type":"book-chapter","created":{"date-parts":[[2022,7,21]],"date-time":"2022-07-21T19:03:55Z","timestamp":1658430235000},"page":"60-74","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Detection and Classification of Paddy Leaf Diseases Using Deep Learning (CNN)"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1836-1117","authenticated-orcid":false,"given":"S.","family":"Maheswaran","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4571-0247","authenticated-orcid":false,"given":"S.","family":"Sathesh","sequence":"additional","affiliation":[]},{"given":"P.","family":"Rithika","sequence":"additional","affiliation":[]},{"given":"I. Mohammed","family":"Shafiq","sequence":"additional","affiliation":[]},{"given":"S.","family":"Nandita","sequence":"additional","affiliation":[]},{"given":"R. D.","family":"Gomathi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,7,22]]},"reference":[{"issue":"10","key":"6_CR1","first-page":"07","volume":"3","author":"M Mukherjee","year":"2012","unstructured":"Mukherjee, M., Pal, T., Samanta, D.: Damaged paddy leaf detection using image processing. J. Global Res. Comput. Sci. 3(10), 07\u201310 (2012)","journal-title":"J. Global Res. Comput. Sci."},{"key":"6_CR2","unstructured":"Bakar, M.A., Abdullah, A., Rahim, N.A., Yazid, H., Misman, S., Masnan, M.: Rice leaf blast disease detection using multi-level colour image thresholding. J. Telecommun. Electron. Comput. Eng. 10(1\u201315), 1\u20136 (2018)"},{"issue":"3","key":"6_CR3","first-page":"460","volume":"2","author":"S Phadikar","year":"2012","unstructured":"Phadikar, S., Sil, J., Das, A.K.: Classification of rice leaf diseases based on morphological changes. Int. J. Inf. Electron. Eng. 2(3), 460\u2013463 (2012)","journal-title":"Int. J. Inf. Electron. Eng."},{"key":"6_CR4","doi-asserted-by":"crossref","unstructured":"Khirade, S.D., Patil, A.: Plant disease detection using image processing. 2015 International Conference on Computing Communication Control and Automation. IEEE (2015)","DOI":"10.1109\/ICCUBEA.2015.153"},{"issue":"01","key":"6_CR5","first-page":"239","volume":"7","author":"T Suman","year":"2015","unstructured":"Suman, T., Dhruvakumar, T.: Classification of paddy leaf diseases using shape and color features. IJEEE. 7(01), 239\u2013250 (2015)","journal-title":"IJEEE."},{"issue":"2","key":"6_CR6","first-page":"249","volume":"7","author":"S Ramesh","year":"2020","unstructured":"Ramesh, S., Vydeki, D.: Recognition and classification of paddy leaf diseases using Optimized Deep Neural network with Jaya algorithm. Inf. Process. Agric. 7(2), 249\u2013260 (2020)","journal-title":"Inf. Process. Agric."},{"issue":"14","key":"6_CR7","first-page":"879","volume":"119","author":"G Saradhambal","year":"2018","unstructured":"Saradhambal, G., Dhivya, R., Latha, S., Rajesh, R.: Plant disease detection and its solution using image classification. Int. J. Pure Appl. Math. 119(14), 879\u2013884 (2018)","journal-title":"Int. J. Pure Appl. Math."},{"key":"6_CR8","doi-asserted-by":"crossref","unstructured":"Ahmed, K., Shahidi, T.R., Alam, S.M.I., Momen, S.: Rice leaf disease detection using machine learning techniques. In: 2019 International Conference on Sustainable Technologies for Industry 40 (STI). IEEE (2019)","DOI":"10.1109\/STI47673.2019.9068096"},{"key":"6_CR9","doi-asserted-by":"crossref","unstructured":"Devaraj, A., Rathan, K., Jaahnavi, S., Indira, K.: Identification of plant disease using image processing technique. In: 2019 International Conference on Communication and Signal Processing (ICCSP). IEEE (2019)","DOI":"10.1109\/ICCSP.2019.8698056"},{"issue":"2","key":"6_CR10","doi-asserted-by":"publisher","first-page":"267","DOI":"10.3923\/itj.2011.267.275","volume":"10","author":"D Al Bashish","year":"2011","unstructured":"Al Bashish, D., Braik, M., Bani-Ahmad, S.: Detection and classification of leaf diseases using K-means-based segmentation and. Inf. Technol. J. 10(2), 267\u2013275 (2011)","journal-title":"Inf. Technol. J."},{"key":"6_CR11","doi-asserted-by":"crossref","unstructured":"Maheswaran, S., Sathesh, S., Priyadharshini, P., Vivek, B.: Identification of artificially ripened fruits using smart phones. In: International Conference on Intelligent Computing and Control 2017 (I2C2) (2017)","DOI":"10.1109\/I2C2.2017.8321857"},{"key":"6_CR12","unstructured":"Amara, J., Bouaziz, B., Algergawy, A.: A deep learning-based approach for banana leaf diseases classification. Datenbanksysteme f\u00fcr Business, Technologie und Web (BTW 2017)-Workshopband (2017)"},{"key":"6_CR13","doi-asserted-by":"crossref","unstructured":"Hari, S.S., Sivakumar, M., Renuga, P., Suriya, S.: Detection of plant disease by leaf image using convolutional neural network. In: 2019 International Conference on Vision Towards Emerging Trends in Communication and Networking (ViTECoN). IEEE (2019)","DOI":"10.1109\/ViTECoN.2019.8899748"},{"issue":"1","key":"6_CR14","first-page":"599","volume":"2","author":"SB Dhaygude","year":"2013","unstructured":"Dhaygude, S.B., Kumbhar, N.P.: Agricultural plant leaf disease detection using image processing. Int. J. Adv. Res. Electric. Electron. Instrum. Eng. 2(1), 599\u2013602 (2013)","journal-title":"Int. J. Adv. Res. Electric. Electron. Instrum. Eng."},{"issue":"1","key":"6_CR15","first-page":"31","volume":"17","author":"H Al-Hiary","year":"2011","unstructured":"Al-Hiary, H., Bani-Ahmad, S., Reyalat, M., Braik, M., Alrahamneh, Z.: Fast and accurate detection and classification of plant diseases. Int. J. Comput. Appl.. 17(1), 31\u201338 (2011)","journal-title":"Int. J. Comput. Appl.."},{"key":"6_CR16","doi-asserted-by":"crossref","unstructured":"Pratapagiri, S., Gangula, R., Ravi, G., Srinivasulu, B., Sowjanya, B., Thirupathi, L.: Early detection of plant leaf disease using convolutional neural networks. In: 2021 3rd International Conference on Electronics Representation and Algorithm (ICERA). IEEE (2021)","DOI":"10.1109\/ICERA53111.2021.9538659"},{"key":"6_CR17","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1016\/j.compag.2018.01.009","volume":"145","author":"KP Ferentinos","year":"2018","unstructured":"Ferentinos, K.P.: Deep learning models for plant disease detection and diagnosis. Comput. Electron. Agric. 145, 311\u2013318 (2018)","journal-title":"Comput. Electron. Agric."},{"key":"6_CR18","doi-asserted-by":"crossref","unstructured":"Sathesh, S., Pradheep, V.A., Maheswaran, S., Premkumar, P., Gokul, N.S., Sriram, P.: Computer vision based real time tracking system to identify overtaking vehicles for safety precaution using single board computer. J. Adv. Res. Dyn. Control Syst. 12(07-Special Issue), 1551\u20131561 (2020)","DOI":"10.5373\/JARDCS\/V12SP7\/20202258"},{"issue":"1","key":"6_CR19","first-page":"211","volume":"15","author":"S Arivazhagan","year":"2013","unstructured":"Arivazhagan, S., Shebiah, R.N., Ananthi, S., Varthini, S.V.: Detection of unhealthy region of plant leaves and classification of plant leaf diseases using texture features. Agric. Eng. Int. CIGR J. 15(1), 211\u2013217 (2013)","journal-title":"Agric. Eng. Int. CIGR J."},{"key":"6_CR20","doi-asserted-by":"crossref","unstructured":"Maheswaran, S., Sathesh, S., Saran, G., Vivek, B.: Automated coconut tree climber. In: International Conference on Intelligent Computing and Control 2017 (I2C2) (2017)","DOI":"10.1109\/I2C2.2017.8321858"},{"issue":"2","key":"6_CR21","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, V.H.C.: Seasonal crops disease prediction and classification using deep convolutional encoder network. Circuits Syst. Sig. Process 39(2), 818\u2013836 (2020)","journal-title":"Circuits Syst. Sig. Process"}],"container-title":["IFIP Advances in Information and Communication Technology","Computer, Communication, and Signal Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-11633-9_6","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,21]],"date-time":"2022-07-21T19:05:17Z","timestamp":1658430317000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-11633-9_6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031116322","9783031116339"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-11633-9_6","relation":{},"ISSN":["1868-4238","1868-422X"],"issn-type":[{"value":"1868-4238","type":"print"},{"value":"1868-422X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"22 July 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICCCSP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computer, Communication, and Signal Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chennai","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":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 February 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 February 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icccsp2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.icccsp.com\/2022\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"111","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"21","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"19% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Conference was held virtually due to COVID-19 pandemic.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}