A Semantic Segmentation Method for Panoramic Water Image
A panoramic image and semantic segmentation technology, applied in the field of computer vision recognition, can solve problems such as slow speed and poor segmentation of small-area targets, and achieve the effects of avoiding gradient attenuation, improving network segmentation accuracy, and improving segmentation accuracy
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[0038] A method for semantic segmentation of water surface panoramic images, comprising:
[0039]Input the panoramic image of the water surface to be tested into the convolutional neural network for real-time semantic segmentation, and obtain the segmentation result of the panoramic image of the water surface;
[0040] like figure 2 As shown in (a), the traditional convolutional neural network uses a convolution with a length and a width of 3, and the size of the traditional convolution kernel is 3*3. The present invention uses two sizes of 3*1 and 1*3 respectively. The convolution kernel, such as figure 2 As shown in (b), the convolutional neural network sets skip connections every 4 convolutional layers.
[0041] When the number of input convolutional layer channels is c1 and the number of output volume base layer channels is c2, the calculation amount of traditional convolution is:
[0042] 3*3*c1*c2=9*c1*c2
[0043] The convolution calculation amount of the present i...
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