Each fold served as a validation set once, while the remaining four folds constituted the training set (25). We used the VGG16 architecture, which is a well-known deep CNN model pre-trained on the ...

VGG16, however, was the least effective, with a precision rate of 83.25%, an F1 score of 83.25%, and a recall of 85.47%. These results confirm the superiority of the Xception model in detecting mango ...

Figure 2 depicts the augmented image. VGG16 architectureis the most outstanding vision network architecture around. The unique feature ofthe VGG16 is its focuson using 3x3 filter convolution layers ...

Abstract: This study focuses on the importance of the classification of citrus leaf diseases from images by utilizing the VGG16 Convolutional Neural Network (CNN) architecture. The objective of this ...

This approach allows us to use fewer resources while still achieving good results with our models [11] . VGG16 is a convolutional neural network (CNN) architecture [12] developed by the Visual ...

The SE-VGG16 model uses VGG16 as the basis and adds the SE attention mechanism to realize that the network automatically focuses on useful parts and allocates limited information processing resources ...