Shafaq Abbas1, Muhammad Attique Khan1, Majed Alhaisoni2, Usman Tariq3, Ammar Armghan4, Fayadh Alenezi4, Arnab Majumdar5, Orawit Thinnukool6,*
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1139-1159, 2023, DOI:10.32604/cmc.2023.028824
Abstract Manual diagnosis of crops diseases is not an easy process; thus, a computerized method is widely used. From a couple of years, advancements in the domain of machine learning, such as deep learning, have shown substantial success. However, they still faced some challenges such as similarity in disease symptoms and irrelevant features extraction. In this article, we proposed a new deep learning architecture with optimization algorithm for cucumber and potato leaf diseases recognition. The proposed architecture consists of five steps. In the first step, data augmentation is performed to increase the numbers of training samples. In the second step, pre-trained… More >
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