Visual saliency detection method based on semantic enhanced convolutional neural network
A convolutional neural network and detection method technology, applied in the design field of visual saliency detection methods, can solve the problem of inability to extract deep image features, and achieve the effects of speeding up training, reducing overfitting, and enhancing semantics
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[0029] Exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be understood that the implementations shown and described in the drawings are only exemplary, intended to explain the principle and spirit of the present invention, rather than limit the scope of the present invention.
[0030] Embodiments of the present invention provide a visual saliency detection method based on a semantically enhanced convolutional neural network, such as figure 1 As shown, the following steps S1-S3 are included:
[0031] S1. Construct a semantically enhanced convolutional neural network based on the VGG16 network.
[0032] In the embodiment of the present invention, the semantically enhanced convolutional neural network is improved on the basis of the VGG16 network. As a classic convolutional neural network model, the VGG16 network has a good performance in image classification and semantic segmentation. The mode...
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