{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T17:43:12Z","timestamp":1790012592954,"version":"4.0.1"},"reference-count":42,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,1,31]],"date-time":"2023-01-31T00:00:00Z","timestamp":1675123200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100015690","name":"Associate Professor Acceleration Research 2022, Universitas Padjadjaran","doi-asserted-by":"publisher","award":["2203\/UN6.3.1\/PT.00\/2022"],"award-info":[{"award-number":["2203\/UN6.3.1\/PT.00\/2022"]}],"id":[{"id":"10.13039\/501100015690","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computation"],"abstract":"<jats:p>In Indonesia, tomato is one of the horticultural products with the highest economic value. To maintain enhanced tomato plant production, it is necessary to monitor the growth of tomato plants, particularly the leaves. The quality and quantity of tomato plant production can be preserved with the aid of computer technology. It can identify diseases in tomato plant leaves. An algorithm for deep learning with a DenseNet architecture was implemented in this study. Multiple hyperparameter tests were conducted to determine the optimal model. Using two hidden layers, a DenseNet trainable layer on dense block 5, and a dropout rate of 0.4, the optimal model was constructed. The 10-fold cross-validation evaluation of the model yielded an accuracy value of 95.7 percent and an F1-score of 95.4 percent. To recognize tomato plant leaves, the model with the best assessment results was implemented in a mobile application.<\/jats:p>","DOI":"10.3390\/computation11020020","type":"journal-article","created":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T02:06:44Z","timestamp":1675217204000},"page":"20","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["Mobile Application for Tomato Plant Leaf Disease Detection Using a Dense Convolutional Network Architecture"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8539-3311","authenticated-orcid":false,"given":"Intan Nurma","family":"Yulita","sequence":"first","affiliation":[{"name":"Research Center for Artificial Intelligence and Big Data, Universitas Padjadjaran, Sumedang 45363, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Naufal Ariful","family":"Amri","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Sumedang 45363, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Akik","family":"Hidayat","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Sumedang 45363, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"104189","DOI":"10.1016\/j.landusepol.2019.104189","article-title":"Does social capital matter in climate change adaptation? 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