A Lightweight Attention-Based Convolutional Neural Networks for Tomato Leaf Disease Classification

• Published in: Agriculture (Basel) Vol. 12; no. 2; p. 228
• Main Authors: Bhujel, Anil, Kim, Na-Eun, Arulmozhi, Elanchezhian, Basak, Jayanta Kumar, Kim, Hyeon-Tae
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.02.2022
• Subjects: Accuracy; agriculture; Artificial neural networks; attention module; Classification; Complexity; Computer applications; Computer vision; convolutional neural networks; Data collection; Datasets; Deep learning; Design; Disease detection; foliar diseases; Food production; Food safety; Leaves; lightweight network; Mathematical models; Modules; Neural networks; Parameters; Performance enhancement; Plant diseases; plant pathology; Plant protection; Recall; tomato disease; Tomatoes

Plant diseases pose a significant challenge for food production and safety. Therefore, it is indispensable to correctly identify plant diseases for timely intervention to protect crops from massive losses. The application of computer vision technology in phytopathology has increased exponentially du...