Dermatological image comparison and classification method, storage medium and robot based on deep learning

Abstract

The invention discloses a deep learning method for comparing and classifying skin disease pictures, a storage medium and a robot. The key points of the technical solution are as follows: S100, classify skin disease pictures into training pictures; S200, perform data enhancement processing on all training pictures; S300, input training pictures in the picture database into convolution Continuously train in the neural network; S400, optimize the convolutional neural network according to the weight loss calculated by the loss function, stop training and fix the weight after obtaining the optimal convolutional neural network; S500, input the patient photos that need to be classified The optimal convolutional neural network model is used for classification, and the result of image classification is obtained. It achieves the effect of automatically training to classify pictures, greatly improving the efficiency of picture classification to improve the triage rate.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a deep learning method for comparing and classifying skin disease pictures, a storage medium and a robot. Background technique [0002] Dermatosis is a general term for diseases that occur on the skin and skin appendages. There are many types of skin diseases, and common skin diseases include: viral, bacterial, fungal and allergic skin diseases. The identification and process qualitative analysis of skin diseases is a huge workload. [0003] The existing Chinese patent with the publication number CN107247958A discloses a method for extracting skin disease features based on image recognition. The method includes the following steps: firstly, preprocessing the sample skin disease pictures acquired, and then vertically segmenting the images and Carry out the corresponding geometric transformation, on this basis, extract the feature area of ​​different types of skin diseas...

AI Technical Summary

Problems solved by technology

[0004] The above existing technical solutions have the following defects: when using the classification algorithm for extracting features to classify images, professional personnel are required to intervene to set the features, and because it is difficult to extract high-quality features, the classification algorithm for manually extracting features It takes a long time and reduces the efficiency of triage, so it needs to be improved

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