{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T21:33:13Z","timestamp":1776547993381,"version":"3.51.2"},"publisher-location":"Singapore","reference-count":17,"publisher":"Springer Singapore","isbn-type":[{"value":"9789811563522","type":"print"},{"value":"9789811563539","type":"electronic"}],"license":[{"start":{"date-parts":[[2020,11,10]],"date-time":"2020-11-10T00:00:00Z","timestamp":1604966400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,11,10]],"date-time":"2020-11-10T00:00:00Z","timestamp":1604966400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-981-15-6353-9_5","type":"book-chapter","created":{"date-parts":[[2020,11,9]],"date-time":"2020-11-09T12:06:39Z","timestamp":1604923599000},"page":"49-55","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Automatic Detection and Classification of Tomato Pests Using Support Vector Machine Based on HOG and LBP Feature Extraction Technique"],"prefix":"10.1007","author":[{"given":"Gayatri","family":"Pattnaik","sequence":"first","affiliation":[]},{"given":"K.","family":"Parvathi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,11,10]]},"reference":[{"issue":"9","key":"5_CR1","doi-asserted-by":"crossref","first-page":"2022","DOI":"10.3390\/s17092022","volume":"17","author":"A Fuentes","year":"2017","unstructured":"Fuentes, A., Yoon, S., Kim, S., Park, D.: A robust deep-learning-based detector for real-time tomato plant diseases and pests recognition. J. Sens 17(9), 2022 (2017)","journal-title":"J. Sens"},{"issue":"3","key":"5_CR2","first-page":"189","volume":"3","author":"JL Miranda","year":"2014","unstructured":"Miranda, J.L., Gerardo, B.D., Tanguilig III, B.T.: Pest detection and extraction using image processing techniques. J. Comp. Comm. Eng. 3(3), 189 (2014)","journal-title":"J. Comp. Comm. Eng."},{"issue":"3","key":"5_CR3","first-page":"190","volume":"11","author":"D Xiao","year":"2018","unstructured":"Xiao, D., Feng, J., Lin, T., Pang, C., Ye, Y.: Classification and recognition scheme for vegetable pests based on the BOF-SVM model. J. Agricult. Biol. Eng. 11(3), 190\u2013196 (2018)","journal-title":"J. Agricult. Biol. Eng."},{"key":"5_CR4","doi-asserted-by":"crossref","unstructured":"Alfarisy, A.A., Chen, Q., Guo, M.: Deep learning based classification for paddy pests & diseases recognition. International. Conference on Mathematics and Artificial Intelligence, pp. 21\u201325 ACM (2018)","DOI":"10.1145\/3208788.3208795"},{"key":"5_CR5","unstructured":"Al-Hiary, H., Bani-Ahmad, S., Reyalat, M., Braik, M., Rahamneh, Z.: Fast and accurate detection and classification of plant diseases. J. Comp. Appl. 17(1), 31\u201338 (2011)"},{"issue":"2","key":"5_CR6","first-page":"77","volume":"2","author":"G Bhadane","year":"2013","unstructured":"Bhadane, G., Sharma, S., Nerkar, V.B.: Early pest identification in agricultural crops using image processing techniques. J. Elect. Elect. Comput. Eng. 2(2), 77\u201382 (2013)","journal-title":"J. Elect. Elect. Comput. Eng."},{"issue":"1","key":"5_CR7","doi-asserted-by":"crossref","first-page":"660","DOI":"10.1186\/2193-1801-2-660","volume":"2","author":"JGA Barbedo","year":"2013","unstructured":"Barbedo, J.G.A.: Digital image processing techniques for detecting, quantifying and classifying plant diseases. Springer Plus 2(1), 660 (2013)","journal-title":"Springer Plus"},{"key":"5_CR8","unstructured":"Krishnan, M., Jabert, G.: Pest control in agricultural plantations using image processing. IOSR J. Elect. Comm. Eng. (IOSR-JECE) 6(4), 68\u201374 (2013)"},{"key":"5_CR9","unstructured":"Mainkar, P.M., Ghorpade, S., Adawadkar, M.: Plant leaf disease detection and classification using image processing techniques. J. Inn. Emer. Res. Eng. 2(4), 139\u2013144 (2015)"},{"key":"5_CR10","unstructured":"Rajan, P., Radhakrishnan, B.: A survey on different image processing techniques for pest identification and plant disease detection. J. Comput. Sci. Net. (IJCSN), 137\u2013141 (2016)"},{"key":"5_CR11","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":"5_CR12","doi-asserted-by":"crossref","unstructured":"Tripathi, M. K., Maktedar, D. D.: Recent machine learning based approaches for disease detection and classification of agricultural products. In: 2016 International Conference on Computing Communication Control and Automation (ICCUBEA), pp. 1\u20136. IEEE (2016)","DOI":"10.1109\/ICCUBEA.2016.7860043"},{"issue":"9","key":"5_CR13","first-page":"950","volume":"3","author":"A Dey","year":"2016","unstructured":"Dey, A., Bhoumik, D., Dey, K.N.: Automatic detection of whitefly pest using statistical feature extraction and image classification methods. Int. Res. J. Eng. Technol. 3(9), 950\u2013959 (2016)","journal-title":"Int. Res. J. Eng. Technol."},{"key":"5_CR14","doi-asserted-by":"crossref","unstructured":"Venugoban, K., Ramanan, A.: Image classification of paddy field insect pests using gradient-based features. Int. J. Mach. Learn. Comput. 4(1) (2014)","DOI":"10.7763\/IJMLC.2014.V4.376"},{"key":"5_CR15","doi-asserted-by":"crossref","unstructured":"Ojala, T., Pietik\u00e4inen, M., M\u00e4enp\u00e4\u00e4, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans. Pattern Anal. Mach. Intell. (7), 971\u2013987 (2002)","DOI":"10.1109\/TPAMI.2002.1017623"},{"key":"5_CR16","doi-asserted-by":"crossref","unstructured":"Laba\u00f1a, F.M., Ruiz, A., Garcia-S\u00e1nchez, F.: PestDetect: pest recognition using convolutional neural network. In: 2nd International Conference on ICTs in Agronomy and Environment, pp. 99\u2013108. Springer, Cham (2019)","DOI":"10.1007\/978-3-030-10728-4_11"},{"key":"5_CR17","doi-asserted-by":"crossref","unstructured":"Boulent, J., Foucher, S., Th\u00e9au, J., St-Charles, P. L: Convolutional Neural Networks for the Automatic Identification of Plant Diseases. Front. Plant Sci. 10 (2019)","DOI":"10.3389\/fpls.2019.00941"}],"container-title":["Advances in Intelligent Systems and Computing","Progress in Advanced Computing and Intelligent Engineering"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-15-6353-9_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,11,9]],"date-time":"2020-11-09T12:11:03Z","timestamp":1604923863000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-981-15-6353-9_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,10]]},"ISBN":["9789811563522","9789811563539"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-981-15-6353-9_5","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"value":"2194-5357","type":"print"},{"value":"2194-5365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,11,10]]},"assertion":[{"value":"10 November 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}