{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T09:52:07Z","timestamp":1742982727223,"version":"3.40.3"},"publisher-location":"Cham","reference-count":12,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030711863"},{"type":"electronic","value":"9783030711870"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"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":[[2021]]},"DOI":"10.1007\/978-3-030-71187-0_45","type":"book-chapter","created":{"date-parts":[[2021,6,2]],"date-time":"2021-06-02T05:04:54Z","timestamp":1622610294000},"page":"488-497","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Analysis of the Superpixel Slic Algorithm for Increasing Data for Disease Detection Using Deep Learning"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9554-8260","authenticated-orcid":false,"given":"Luiz Daniel Garay","family":"Trindade","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4275-0638","authenticated-orcid":false,"given":"F\u00e1bio Paulo","family":"Basso","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3431-2814","authenticated-orcid":false,"given":"Elder","family":"de Macedo Rodrigues","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2776-8020","authenticated-orcid":false,"given":"Maicon","family":"Bernardino","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1560-423X","authenticated-orcid":false,"given":"Daniel","family":"Welfer","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7225-6027","authenticated-orcid":false,"given":"Daniel","family":"M\u00fcller","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,6,3]]},"reference":[{"issue":"11","key":"45_CR1","doi-asserted-by":"publisher","first-page":"2274","DOI":"10.1109\/TPAMI.2012.120","volume":"34","author":"R Achanta","year":"2012","unstructured":"Achanta, R., Shaji, A., Smith, K., Lucchi, A., Fua, P., S\u00fcsstrunk, S.: SLIC superpixels compared to state-of-the-art superpixel methods. IEEE Trans. Pattern Anal. Mach. Intell. 34(11), 2274\u20132282 (2012)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"6","key":"45_CR2","doi-asserted-by":"publisher","first-page":"1749","DOI":"10.1109\/TLA.2018.8444395","volume":"16","author":"JGA Barbedo","year":"2018","unstructured":"Barbedo, J.G.A., Koenigkan, L.V., Halfeld-Vieira, B.A., Costa, R.V., Nechet, K.L., Godoy, C.V., Junior, M.L., Patricio, F.R.A., Talamini, V., Chitarra, L.G., et al.: Annotated plant pathology databases for image-based detection and recognition of diseases. IEEE Lat. Am. Trans. 16(6), 1749\u20131757 (2018)","journal-title":"IEEE Lat. Am. Trans."},{"key":"45_CR3","doi-asserted-by":"publisher","first-page":"941","DOI":"10.3389\/fpls.2019.00941","volume":"10","author":"J Boulent","year":"2019","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, 941 (2019)","journal-title":"Front. Plant Sci."},{"key":"45_CR4","doi-asserted-by":"publisher","first-page":"113588","DOI":"10.1016\/j.eswa.2020.113588","volume":"159","author":"H Cecotti","year":"2020","unstructured":"Cecotti, H., Rivera, A., Farhadloo, M., Villarreal, M.P.: Grape detection with convolutional neural networks. Exp. Syst. Appl. 159, 113588 (2020)","journal-title":"Exp. Syst. Appl."},{"issue":"9","key":"45_CR5","doi-asserted-by":"publisher","first-page":"1337","DOI":"10.1016\/j.cropro.2007.03.022","volume":"26","author":"J Cooper","year":"2007","unstructured":"Cooper, J., Dobson, H.: The benefits of pesticides to mankind and the environment. Crop Prot. 26(9), 1337\u20131348 (2007)","journal-title":"Crop Prot."},{"key":"45_CR6","unstructured":"FAO: How to feed the world 2050. the special challenge for Sub-Saharan Africa. In: High Level Expert Forum (2009)"},{"key":"45_CR7","doi-asserted-by":"publisher","first-page":"323","DOI":"10.1016\/j.compeleceng.2019.04.011","volume":"76","author":"G Geetharamani","year":"2019","unstructured":"Geetharamani, G., Pandian, A.: Identification of plant leaf diseases using a nine-layer deep convolutional neural network. Comput. Electr. Eng. 76, 323\u2013338 (2019)","journal-title":"Comput. Electr. Eng."},{"key":"45_CR8","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1016\/j.compag.2018.02.016","volume":"147","author":"A Kamilaris","year":"2018","unstructured":"Kamilaris, A., Prenafeta-Bold\u00fa, F.X.: Deep learning in agriculture: a survey. Comput. Electron. Agric. 147, 70\u201390 (2018)","journal-title":"Comput. Electron. Agric."},{"key":"45_CR9","doi-asserted-by":"publisher","first-page":"105093","DOI":"10.1016\/j.compag.2019.105093","volume":"167","author":"A Picon","year":"2019","unstructured":"Picon, A., Seitz, M., Alvarez-Gila, A., Mohnke, P., Ortiz-Barredo, A., Echazarra, J.: Crop conditional convolutional neural networks for massive multi-crop plant disease classification over cell phone acquired images taken on real field conditions. Comput. Electron. Agric. 167, 105093 (2019)","journal-title":"Comput. Electron. Agric."},{"key":"45_CR10","doi-asserted-by":"publisher","first-page":"4133","DOI":"10.1007\/s00521-020-05235-5","volume":"33","author":"S U\u011fuz","year":"2020","unstructured":"U\u011fuz, S., Uysal, N.: Classification of olive leaf diseases using deep convolutional neural networks. Neural Comput. Appl. 33, 4133\u20134149 (2020)","journal-title":"Neural Comput. Appl."},{"key":"45_CR11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-29044-2","volume-title":"Experimentation in software engineering","author":"C Wohlin","year":"2012","unstructured":"Wohlin, C., Runeson, P., H\u00f6st, M., Ohlsson, M.C., Regnell, B., Wessl\u00e9n, A.: Experimentation in software engineering. Springer, Heidelberg (2012)"},{"issue":"4","key":"45_CR12","doi-asserted-by":"publisher","first-page":"659","DOI":"10.1007\/s40030-019-00390-y","volume":"100","author":"Q Wu","year":"2019","unstructured":"Wu, Q., Zhang, K., Meng, J.: Identification of soybean leaf diseases via deep learning. J. Inst. Eng. (India) Ser. A 100(4), 659\u2013666 (2019)","journal-title":"J. Inst. Eng. (India) Ser. A"}],"container-title":["Advances in Intelligent Systems and Computing","Intelligent Systems Design and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-71187-0_45","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,6,2]],"date-time":"2021-06-02T05:16:46Z","timestamp":1622611006000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-71187-0_45"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030711863","9783030711870"],"references-count":12,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-71187-0_45","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"type":"print","value":"2194-5357"},{"type":"electronic","value":"2194-5365"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"3 June 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ISDA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Systems Design and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 December 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 December 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"isda2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.mirlabs.net\/isda20\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}