Skin disease detecting method based on deep learning and system thereof
A skin disease and deep learning technology, applied in the field of skin disease detection system based on deep learning, can solve problems such as poor professionalism and poor consultation effect, and achieve the effect of improving detection effect and performance
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Embodiment 1
[0039] reference figure 1 , The first embodiment discloses a skin disease detection method based on deep learning, the method includes:
[0040] S100. Before the neural network model performs skin detection, use pictures marked with disease areas and disease types of skin diseases as training data, and train an improved Faster RCNN neural network model after preprocessing;
[0041] Among them, the neural network model uses a deep-width residual network to perform feature extraction on the input image, and the extracted feature image is used as a shared feature of the disease area and the disease type to achieve two optimization goals while learning.
[0042] S200. When performing skin detection, preprocess the picture of the skin to be detected and input it into an improved Faster RCNN neural network model, which outputs the disease area and disease type of the skin to be detected.
[0043] reference figure 2 Specifically, the neural network model in this embodiment includes:
[0044] ...
Embodiment 2
[0054] Based on the same inventive concept, the present invention also discloses a skin disease detection system based on deep learning. The system disclosed in the second embodiment includes: a picture input layer and an improved Faster RCNN neural network model. Among them, the picture input layer is used to preprocess the input picture and input it into the neural network model, and the neural network model is used to output and detect the disease area and disease type of the skin.
[0055] It should be noted that before the neural network model performs skin detection, pictures with the disease area and disease type labeled with skin diseases can be used as training data, and the neural network model is trained after preprocessing, and the neural network model after training is completed. The network model is ready for use.
[0056] In this embodiment, the neural network model uses a depth-width residual network to perform feature extraction on input pictures, and the extracted...
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