Abstract
The infrared heat map reflects the overall temperature distribution of the human body, which coincides with the theory of traditional Chinese medicine, as an important indicator of human sub-health status identification in the field of traditional Chinese medicine, the physical fitness of traditional Chinese medicine has attracted more and more attention from the medical field and the general public. Because the infrared heat map of the human body has rich color distribution characteristics, this paper uses color feature extraction and texture feature extraction algorithms combined with SVM classifiers and convolutional neural networks to perform classification experiments. The results show that the accuracy of deep learning algorithms is higher than that of traditional machine learning algorithms, Deep learning can be combined with local subtle features for further research.
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