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The identified research challenge is precisely targeted, and the model is developed using a meticulously curated custom dataset. Through comprehensive training, validation, and testing phases, the study ensures the robust performance of the Yolov8 model. The novelty of this research lies in its focused solution to the specific accuracy challenge within deep learning-based tomato leaf disease detection. The proposed methodology is rigorously evaluated through extensive experimentation, showcasing its ability to surpass existing benchmarks and offering a highly effective solution. This innovative approach not only contributes a unique solution to the identified problem but also advances the field by providing a more accurate and reliable method for detecting tomato leaf diseases.<\/jats:p>","DOI":"10.3233\/jifs-236905","type":"journal-article","created":{"date-parts":[[2024,2,16]],"date-time":"2024-02-16T10:43:38Z","timestamp":1708080218000},"page":"7909-7921","source":"Crossref","is-referenced-by-count":11,"title":["Automatic detection of tomato leaf disease using an adopted deep learning algorithm"],"prefix":"10.1177","volume":"46","author":[{"given":"Xu","family":"Guo","sequence":"first","affiliation":[{"name":"College of Electronics and Information, Shanghai Dianji University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","reference":[{"key":"10.3233\/JIFS-236905_ref1","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1007\/s41348-021-00500-8","article-title":"Artificial intelligence in tomato leaf disease detection: a comprehensive review and discussion","volume":"129","author":"Thangaraj","year":"2022","journal-title":"Journal of Plant Diseases and Protection"},{"key":"10.3233\/JIFS-236905_ref2","doi-asserted-by":"crossref","first-page":"140","DOI":"10.3390\/electronics11010140","article-title":"Optimized deep learning algorithms for tomato leaf disease detection with hardware deployment","volume":"11","author":"Tarek","year":"2022","journal-title":"Electronics"},{"key":"10.3233\/JIFS-236905_ref3","doi-asserted-by":"crossref","first-page":"951","DOI":"10.3390\/electronics11060951","article-title":"AlexNet convolutional neural network for disease detection and classification of tomato leaf","volume":"11","author":"Chen","year":"2022","journal-title":"Electronics"},{"key":"10.3233\/JIFS-236905_ref4","doi-asserted-by":"crossref","first-page":"100793","DOI":"10.1016\/j.scp.2022.100793","article-title":"Deep Convolutional Neural Networks for image based tomato leaf disease detection","volume":"30","author":"Anandhakrishnan","year":"2022","journal-title":"Sustainable Chemistry and Pharmacy"},{"key":"10.3233\/JIFS-236905_ref8","doi-asserted-by":"crossref","first-page":"e0195418","DOI":"10.1371\/journal.pone.0195418","article-title":"Correction: A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos","volume":"13","author":"Aghamohammadi","year":"2018","journal-title":"Plos One"},{"key":"10.3233\/JIFS-236905_ref10","first-page":"100441","article-title":"A comprehensive review on detection of plant disease using machine learning and deep learning approaches,","author":"Jackulin","year":"2022","journal-title":"Measurement: Sensors"},{"key":"10.3233\/JIFS-236905_ref12","doi-asserted-by":"crossref","first-page":"105951","DOI":"10.1016\/j.compag.2020.105951","article-title":"L.E.Amabilis-Sosa, B. 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