{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T05:37:17Z","timestamp":1778218637029,"version":"3.51.4"},"reference-count":35,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2025,7,31]],"date-time":"2025-07-31T00:00:00Z","timestamp":1753920000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>Potatoes are one of the world\u2019s most widely cultivated crops, but their yield is coming under mounting pressure from early blight, a fungal disease caused by Alternaria solani. Early detection and accurate identification are key to effective disease management and yield protection. This paper introduces a novel deep learning framework called ZeroShot CNN, which integrates convolutional neural networks (CNNs) and ZeroShot Learning (ZSL) for the efficient classification of seen and unseen disease classes. The model utilizes convolutional layers for feature extraction and employs semantic embedding techniques to identify previously untrained classes. Implemented on the Kaggle potato disease dataset, ZeroShot CNN achieved 98.50% accuracy for seen categories and 99.91% accuracy for unseen categories, outperforming conventional methods. The hybrid approach demonstrated superior generalization, providing a scalable, real-time solution for detecting agricultural diseases. The success of this solution validates the potential in harnessing deep learning and ZeroShot inference to transform plant pathology and crop protection practices.<\/jats:p>","DOI":"10.3390\/jimaging11080256","type":"journal-article","created":{"date-parts":[[2025,8,4]],"date-time":"2025-08-04T11:54:51Z","timestamp":1754308491000},"page":"256","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Advancing Early Blight Detection in Potato Leaves Through ZeroShot Learning"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4095-8868","authenticated-orcid":false,"given":"Muhammad Shoaib","family":"Farooq","sequence":"first","affiliation":[{"name":"Department of Computer Science, School of Systems and Technology, University of Management and Technology, Lahore 54000, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ayesha","family":"Kamran","sequence":"additional","affiliation":[{"name":"Department of Computer Science, School of Systems and Technology, University of Management and Technology, Lahore 54000, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5410-353X","authenticated-orcid":false,"given":"Syed Atir","family":"Raza","sequence":"additional","affiliation":[{"name":"Department of Applied Computing Technologies FoIT& CS, University of Central Punjab Lahore, Lahore 54000, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Muhammad Farooq","family":"Wasiq","sequence":"additional","affiliation":[{"name":"METICS Solutions Ltd., London IG3 9JA, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bilal","family":"Hassan","sequence":"additional","affiliation":[{"name":"Faculty of Engineering & Environment, Northumbria University, London Campus, London E1 7HT, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4503-615X","authenticated-orcid":false,"given":"Nitsa J.","family":"Herzog","sequence":"additional","affiliation":[{"name":"Faculty of Engineering & Environment, Northumbria University, London Campus, London E1 7HT, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1007\/s12230-018-09705-4","article-title":"Potatoes, nutrition and health","volume":"96","author":"Beals","year":"2019","journal-title":"Am. 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