With the development of deep neural network, its excellent performance in the field of vision has attracted the attention of scholars at home and abroad. The method based on convolutional neural network (CNN) has become the most important tool to solve related tasks in the field of vision. In this paper, the weather recognition algorithm based on CNN is studied. This paper first analyzes the structure and characteristics of CNN. Aiming at the problems of low accuracy of existing weather image classification methods and slow model training speed, transfer learning method is introduced on the basis of deep CNN, which can greatly shorten the model training time and obtain better classification effect.

Sitong Lyu. Weather Recognition Algorithm based on Convolution Neural Network. International Journal of Neural Network (2020), Vol. 1, Issue 1: 24-30. https://doi.org/10.38007/NN.2020.010104.

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