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- W4289816675 abstract "Eggplant is a popular vegetable crop. Eggplant yields can be affected by various diseases. Automatic detection and recognition of diseases is an important step toward improving crop yields. In this paper, we used a two-stream deep fusion architecture, employing CNN-SVM and CNN-Softmax pipelines, along with an inference model to infer the disease classes. A dataset of 2284 images was sourced from primary (using a consumer RGB camera) and secondary sources (the internet). The dataset contained images of nine eggplant diseases. Experimental results show that the proposed method achieved better accuracy and lower false-positive results compared to other deep learning methods (such as VGG16, Inception V3, VGG 19, MobileNet, NasNetMobile, and ResNet50)." @default.
- W4289816675 created "2022-08-05" @default.
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- W4289816675 date "2022-08-04" @default.
- W4289816675 modified "2023-10-14" @default.
- W4289816675 title "Deep Network with Score Level Fusion and Inference-Based Transfer Learning to Recognize Leaf Blight and Fruit Rot Diseases of Eggplant" @default.
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- W4289816675 doi "https://doi.org/10.3390/agriculture12081160" @default.
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