{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T05:06:03Z","timestamp":1773119163474,"version":"3.50.1"},"reference-count":12,"publisher":"Wiley","license":[{"start":{"date-parts":[[2019,5,5]],"date-time":"2019-05-05T00:00:00Z","timestamp":1557014400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000807","name":"European GNSS Agency","doi-asserted-by":"publisher","award":["776324"],"award-info":[{"award-number":["776324"]}],"id":[{"id":"10.13039\/501100000807","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Sensors"],"published-print":{"date-parts":[[2019,5,5]]},"abstract":"<jats:p>Greenhouse crop production is growing throughout the world and early pest detection is of particular importance in terms of productivity and reduction of the use of pesticides. Conventional eye observation methods are nonefficient for large crops. Computer vision and recent advances in deep learning can play an important role in increasing the reliability and productivity. This paper presents the development and comparison of two different approaches for vision based automated pest detection and identification, using learning strategies. A solution that combines computer vision and machine learning is compared against a deep learning solution. The main focus of our work is on the selection of the best approach based on pest detection and identification accuracy. The inspection is focused on the most harmful pests on greenhouse tomato and pepper crops,<jats:italic> Bemisia tabaci<\/jats:italic> and<jats:italic> Trialeurodes vaporariorum<\/jats:italic>. A dataset with a huge number of infected tomato plants images was created to generate and evaluate machine learning and deep learning models. The results showed that the deep learning technique provides a better solution because (a) it achieves the disease detection and classification in one step, (b) gets better accuracy, (c) can distinguish better between<jats:italic> Bemisia tabaci<\/jats:italic> and<jats:italic> Trialeurodes vaporariorum<\/jats:italic>, and (d) allows balancing between speed and accuracy by choosing different models.<\/jats:p>","DOI":"10.1155\/2019\/5219471","type":"journal-article","created":{"date-parts":[[2019,5,6]],"date-time":"2019-05-06T11:12:48Z","timestamp":1557141168000},"page":"1-15","source":"Crossref","is-referenced-by-count":98,"title":["A Benchmarking of Learning Strategies for Pest Detection and Identification on Tomato Plants for Autonomous Scouting Robots Using Internal Databases"],"prefix":"10.1155","volume":"2019","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8500-5294","authenticated-orcid":true,"given":"Aitor","family":"Gutierrez","sequence":"first","affiliation":[{"name":"Autonomous and Intelligent Systems Unit, IK4-Tekniker, Eibar, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ander","family":"Ansuategi","sequence":"additional","affiliation":[{"name":"Autonomous and Intelligent Systems Unit, IK4-Tekniker, Eibar, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Loreto","family":"Susperregi","sequence":"additional","affiliation":[{"name":"Autonomous and Intelligent Systems Unit, IK4-Tekniker, Eibar, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Carlos","family":"Tub\u00edo","sequence":"additional","affiliation":[{"name":"Autonomous and Intelligent Systems Unit, IK4-Tekniker, Eibar, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ivan","family":"Ranki\u0107","sequence":"additional","affiliation":[{"name":"Department of Chemistry and Biochemistry, Faculty of AgriSciences, Mendel University, Brno, Czech Republic"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Libor","family":"Len\u017ea","sequence":"additional","affiliation":[{"name":"Department of Chemistry and Biochemistry, Faculty of AgriSciences, Mendel University, Brno, Czech Republic"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"9","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2018.02.016"},{"key":"18","first-page":"137","year":"2016","journal-title":"International Journal of Computer Science and Network (IJCSN)"},{"key":"22","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"21","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2010.06.009"},{"key":"28","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10590-1_53"},{"key":"15","doi-asserted-by":"publisher","DOI":"10.1007\/978-81-322-2250-7_77"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0123262"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1155\/2014\/214674"},{"issue":"4","key":"2","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1080\/08839514.2017.1315516","volume":"31","year":"2017","journal-title":"Applied Artificial Intelligence"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.3389\/fpls.2016.01419"},{"key":"19","first-page":"91","year":"2015","journal-title":"Advances in Neural Information Processing Systems"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-009-0275-4"}],"container-title":["Journal of Sensors"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/js\/2019\/5219471.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/js\/2019\/5219471.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/js\/2019\/5219471.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,6]],"date-time":"2019-05-06T11:12:52Z","timestamp":1557141172000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/js\/2019\/5219471\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,5,5]]},"references-count":12,"alternative-id":["5219471","5219471"],"URL":"https:\/\/doi.org\/10.1155\/2019\/5219471","relation":{},"ISSN":["1687-725X","1687-7268"],"issn-type":[{"value":"1687-725X","type":"print"},{"value":"1687-7268","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,5,5]]}}}