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Deep learning, the latest breakthrough in computer vision, is promising for fine-grained disease severity classification, as the method avoids the labor-intensive feature engineering and threshold-based segmentation. Using the apple black rot images in the PlantVillage dataset, which are further annotated by botanists with four severity stages as ground truth, a series of deep convolutional neural networks are trained to diagnose the severity of the disease. The performances of shallow networks trained from scratch and deep models fine-tuned by transfer learning are evaluated systemically in this paper. The best model is the deep VGG16 model trained with transfer learning, which yields an overall accuracy of 90.4% on the hold-out test set. The proposed deep learning model may have great potential in disease control for modern agriculture.<\/jats:p>","DOI":"10.1155\/2017\/2917536","type":"journal-article","created":{"date-parts":[[2017,7,5]],"date-time":"2017-07-05T21:02:24Z","timestamp":1499288544000},"page":"1-8","source":"Crossref","is-referenced-by-count":541,"title":["Automatic Image-Based Plant Disease Severity Estimation Using Deep Learning"],"prefix":"10.1155","volume":"2017","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3568-2908","authenticated-orcid":true,"given":"Guan","family":"Wang","sequence":"first","affiliation":[{"name":"School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3206-9515","authenticated-orcid":true,"given":"Yu","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1320-3969","authenticated-orcid":true,"given":"Jianxin","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1080\/07352681003617285"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.3389\/fpls.2014.00734"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.4172\/2329-6577.1000e111"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1094\/PHYTO-11-13-0328-R"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1094\/PDIS-03-14-0290-RE"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2015.11.021"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0168274"},{"key":"8","doi-asserted-by":"publisher","DOI":"10.5120\/2183-2754"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2014.05.033"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1155\/2014\/214674"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1117\/1.3651799"},{"key":"12","year":"2010","journal-title":"Probabilistic classification of disease symptoms caused by Salmonella on Arabidopsis plants, presented at the GI Jahrestagung"},{"key":"13","doi-asserted-by":"publisher","DOI":"10.1007\/s10658-016-1007-6"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.1094\/AssessHelp"},{"key":"15","doi-asserted-by":"publisher","DOI":"10.1094\/PDIS-03-15-0319-RE"},{"key":"16","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2012.2205597"},{"key":"18","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2577031"},{"key":"20","doi-asserted-by":"publisher","DOI":"10.1002\/minf.201501008"},{"key":"21","doi-asserted-by":"publisher","DOI":"10.1038\/nbt.3300"},{"key":"26","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2017.01.018"},{"key":"27"},{"key":"29","doi-asserted-by":"publisher","DOI":"10.1155\/2016\/3289801"},{"key":"30","doi-asserted-by":"publisher","DOI":"10.3389\/fpls.2016.01419"},{"key":"32","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"}],"container-title":["Computational Intelligence and Neuroscience"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2017\/2917536.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2017\/2917536.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2017\/2917536.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,5,18]],"date-time":"2020-05-18T01:48:44Z","timestamp":1589766524000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/cin\/2017\/2917536\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"references-count":24,"alternative-id":["2917536","2917536"],"URL":"https:\/\/doi.org\/10.1155\/2017\/2917536","relation":{},"ISSN":["1687-5265","1687-5273"],"issn-type":[{"value":"1687-5265","type":"print"},{"value":"1687-5273","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017]]}}}