Research on image classification based on neural network VGG16
Fei Yuan, Xianzhong Jiang, Weisong Du, Weilin Yang · 2023
Based on PyTorch framework, this paper studies the network structure of classical convolutional neural network VGG16 and the process of input image changing in the network. Using VGG16 to train the small dataset CIFAR10 in various ways, it is found that using the Kaiming normal distribution to initialize the weight for training is far less effective than transfer learning (using the training weight of VGG16 on the ImageNet dataset as the initial value of the weight). The input image of VGG16 can be of any size, but after the image of CIFAR10 is resized to 224×224, the accuracy rate on the test set is improved by 6 percentage points.