{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,6]],"date-time":"2025-06-06T04:04:36Z","timestamp":1749182676591,"version":"3.41.0"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031789397","type":"print"},{"value":"9783031789403","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[[2025]]},"DOI":"10.1007\/978-3-031-78940-3_27","type":"book-chapter","created":{"date-parts":[[2025,6,5]],"date-time":"2025-06-05T06:07:39Z","timestamp":1749103659000},"page":"266-274","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["BEiT-Based Deep Model for Agricultural Pest Detection"],"prefix":"10.1007","author":[{"given":"Raghunath","family":"Mandipudi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"A. Basi","family":"Reddy","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Konatham","family":"Sumalatha","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Naresh","family":"Tangudu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Madhavi","family":"Gudavalli","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"K. Mahesh","family":"Kumar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,6,6]]},"reference":[{"key":"27_CR1","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1016\/j.compag.2017.03.016","volume":"137","author":"MA Ebrahimi","year":"2017","unstructured":"Ebrahimi, M.A., Khoshtaghaza, M.H., Minaei, S., Jamshidi, B.: Vision-based pest detection based on SVM classification method. Comput. Electron. Agric. 137, 52\u201358 (2017)","journal-title":"Comput. Electron. Agric."},{"key":"27_CR2","doi-asserted-by":"crossref","unstructured":"Venkatasaichandrakanth, P., Iyapparaja, M.: Pest detection and classification in peanut crops using CNN, MFO, and EViTA algorithms. IEEE Access (2023)","DOI":"10.1109\/ACCESS.2023.3281508"},{"key":"27_CR3","doi-asserted-by":"crossref","unstructured":"Sunitha, G., Madhavi, K.R., Avanija, J., Reddy, S.T.K., Vittal, R.H.S.: Modeling convolutional neural network for detection of plant leaf spot diseases. In: 2022 3rd International Conference on Electronics and Sustainable Communication Systems (ICESC), pp. 1187\u20131192. IEEE (2022)","DOI":"10.1109\/ICESC54411.2022.9885593"},{"issue":"12","key":"27_CR4","doi-asserted-by":"publisher","first-page":"1587","DOI":"10.3390\/e23121587","volume":"23","author":"M Zha","year":"2021","unstructured":"Zha, M., Qian, W., Yi, W., Hua, J.: A lightweight YOLOv4-Based forestry pest detection method using coordinate attention and feature fusion. Entropy 23(12), 1587 (2021)","journal-title":"Entropy"},{"key":"27_CR5","doi-asserted-by":"crossref","unstructured":"Prabhakar, T., Srujan Raju, K., Reddy Madhavi, K.: Support vector machine classification of remote sensing images with the wavelet-based statistical features. In: Proceedings of Fifth International Conference on Smart Computing and Informatics, pp. 603\u2013613. Springer (2022)","DOI":"10.1007\/978-981-16-9705-0_59"},{"key":"27_CR6","doi-asserted-by":"publisher","first-page":"45301","DOI":"10.1109\/ACCESS.2019.2909522","volume":"7","author":"L Liu","year":"2019","unstructured":"Liu, L., et al.: PestNet: an end-to-end deep learning approach for large-scale multi-class pest detection and classification. IEEE Access 7, 45301\u201345312 (2019)","journal-title":"IEEE Access"},{"issue":"4","key":"27_CR7","doi-asserted-by":"publisher","first-page":"372","DOI":"10.3390\/electronics10040372","volume":"10","author":"JW Chen","year":"2021","unstructured":"Chen, J.W., Lin, W.J., Cheng, H.J., Hung, C.L., Lin, C.Y., Chen, S.P.: A smartphone-based application for scale pest detection using multiple-object detection methods. Electronics 10(4), 372 (2021)","journal-title":"Electronics"},{"key":"27_CR8","doi-asserted-by":"crossref","unstructured":"Sunitha, G., Sudeepthi, A., Sreedhar, B., Shaik, A.B., Farooq, C.L.: RetinaNet and vision transformer-based model for wheat head detection. In: 2023 5th International Conference on Inventive Research in Computing Applications (ICIRCA), pp. 151\u2013156. IEEE (2023)","DOI":"10.1109\/ICIRCA57980.2023.10220614"},{"key":"27_CR9","doi-asserted-by":"crossref","unstructured":"Suma, K.G., Aswini, J., Sunitha, G., Balaji, K.: AI-driven applications in high-tech agriculture. In: Handbook of Research on AI-Equipped IoT Applications in High-Tech Agriculture, pp. 23\u201337. IGI Global (2023)","DOI":"10.4018\/978-1-6684-9231-4.ch002"},{"issue":"3","key":"27_CR10","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1111\/jen.12834","volume":"145","author":"DJA Rustia","year":"2021","unstructured":"Rustia, D.J.A., et al.: Automatic greenhouse insect pest detection and recognition based on a cascaded deep learning classification method. J. Appl. Entomol. 145(3), 206\u2013222 (2021)","journal-title":"J. Appl. Entomol."},{"key":"27_CR11","doi-asserted-by":"crossref","unstructured":"Nennuri, R., Kumar, R.H., Prathyusha, G., Tejaswini, K., Kanishka, G., Sunitha, G.: A multi-stage deep model for crop variety and disease prediction. In: International Conference on Soft Computing and Pattern Recognition, pp. 52\u201359. Springer Nature Switzerland, Cham (2022)","DOI":"10.1007\/978-3-031-27524-1_6"},{"key":"27_CR12","doi-asserted-by":"crossref","unstructured":"Dou, Z.Y., et al.: An empirical study of training end-to-end vision-and-language transformers. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 18166\u201318176 (2022)","DOI":"10.1109\/CVPR52688.2022.01763"},{"key":"27_CR13","doi-asserted-by":"crossref","unstructured":"Shereesha, M., Hemavathy, C., Teja, H., Reddy, G.M., Kumar, B.V., Sunitha, G.: Precision mango farming: using compact convolutional transformer for disease detection. In International Conference on Innovations in Bio-Inspired Computing and Applications, pp. 458\u2013465. Springer Nature Switzerland, Cham (2022)","DOI":"10.1007\/978-3-031-27499-2_43"},{"key":"27_CR14","doi-asserted-by":"publisher","unstructured":"Devika, K.D., Saxena, A.: Dynamic Authentication Using Visual Cryptography. In: Satapathy, S.C., Lin, J.CW., Wee, L.K., Bhateja, V., Rajesh, T.M. (eds.) Computer Communication, Networking and IoT. Lecture Notes in Networks and Systems, vol\/ 459. Springer, Singapore (2023). https:\/\/doi.org\/10.1007\/978-981-19-1976-3_20","DOI":"10.1007\/978-981-19-1976-3_20"},{"key":"27_CR15","doi-asserted-by":"publisher","unstructured":"Maithri, Y., Saxena, A.: Browser extension for digital signature. In: Satapathy, S.C., Lin, J.CW., Wee, L.K., Bhateja, V., Rajesh, T.M. (eds.) Computer Communication, Networking and IoT. Lecture Notes in Networks and Systems, vol 459. Springer, Singapore (2023). https:\/\/doi.org\/10.1007\/978-981-19-1976-3_21","DOI":"10.1007\/978-981-19-1976-3_21"},{"key":"27_CR16","doi-asserted-by":"publisher","unstructured":"Singh, A., Tiwari, V., Tentu, A.N., Saxena, A.: Securing communication in IoT environment using lightweight key generation-assisted homomorphic authenticated encryption. In: Satapathy, S.C., Lin, J.CW., Wee, L.K., Bhateja, V., Rajesh, T.M. (eds.) Computer Communication, Networking and IoT. Lecture Notes in Networks and Systems, vol 459. Springer, Singapore (2023). https:\/\/doi.org\/10.1007\/978-981-19-1976-3_26","DOI":"10.1007\/978-981-19-1976-3_26"},{"key":"27_CR17","doi-asserted-by":"publisher","unstructured":"Srujan Raju, K., Jagtap, V., Kulkarni, P., Varaprasad Rao, M. (2023). Gameplay Cognitive Decision Support Using Statistical and Non-statistical Parametric Fusion. In: Satapathy, S.C., Lin, J.CW., Wee, L.K., Bhateja, V., Rajesh, T.M. (eds.) Computer Communication, Networking and IoT. Lecture Notes in Networks and Systems, vol. 459. Springer, Singapore. https:\/\/doi.org\/10.1007\/978-981-19-1976-3_24","DOI":"10.1007\/978-981-19-1976-3_24"},{"key":"27_CR18","doi-asserted-by":"publisher","unstructured":"Kumar Apat, S., Mishra, J., Srujan Raju, K., Padhy, N.:. IoT-Assisted crop monitoring using machine learning algorithms for smart farming. In: Kumar, R., Pattnaik, P.K., R. S. Tavares, J.M. (eds.) Next Generation of Internet of Things. Lecture Notes in Networks and Systems, vol. 445. Springer, Singapore (2023). https:\/\/doi.org\/10.1007\/978-981-19-1412-6_1","DOI":"10.1007\/978-981-19-1412-6_1"},{"issue":"1","key":"27_CR19","doi-asserted-by":"publisher","first-page":"5329","DOI":"10.1038\/s41598-023-32440-8","volume":"13","author":"L Folle","year":"2023","unstructured":"Folle, L., et al.: DeepNAPSI multi-reader nail psoriasis prediction using deep learning. Sci. Rep. 13(1), 5329 (2023)","journal-title":"Sci. Rep."},{"key":"27_CR20","unstructured":"Agricultural Pests Dataset: https:\/\/www.kaggle.com\/datasets\/gauravduttakiit\/agricultural-pests-dataset. Accessed May 2023"}],"container-title":["Lecture Notes in Networks and Systems","Bio-Inspired Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-78940-3_27","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,5]],"date-time":"2025-06-05T06:07:44Z","timestamp":1749103664000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-78940-3_27"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031789397","9783031789403"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-78940-3_27","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"value":"2367-3370","type":"print"},{"value":"2367-3389","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"6 June 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IBICA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Innovations in Bio-Inspired Computing and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Kochi","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":"14 December 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 December 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ibica2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.mirlabs.net\/ibica23\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}