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Published in:
2020 | OriginalPaper | Chapter
Image Classification of Submarine Volcanic Smog Map Based on Convolution Neural Network
Authors : Xiaoting Liu, Li Liu, Yuhui Chen
Published in: Digital TV and Wireless Multimedia Communication
Publisher: Springer Singapore
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Abstract
In order to meet the problem of smoke image classification in submarine volcanic scene, in this paper, depth convolution neural network (Deep Convolutional Neural Networks, DCNN) is used to classify smoke seafloor map and smoke-free seafloor map under small-scale data set and limited computing power. Firstly, the data enhancement technology is used to expand the data set through angle rotation, horizontal flipping, random cutting and adding Gaussian noise, and then the depth convolution neural network is built for training. Finally, the recognition and classification is carried out according to the prediction image label of the classifier. The experimental results show that the classification accuracy of the proposed method is more than 91%.