![]() Wang, X., Zhang, D.: A high quality color imaging system for computerized tongue image analysis. In: 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005, pp. Zhang, H.Z., Wang, K.Q., Zhang, D., et al.: Computer aided tongue diagnosis system. Lao, L., Xu, L., Xu, S.: Traditional Chinese Medicine. Nestler, G., Dovey, M.: Traditional Chinese medicine. Experimental results demonstrate that the proposed method performs better than the method extracting handcraft features. At last, cracked tongue recognition is considered as a multiple instance learning problem, and we train a multiple-instance Support Vector Machine (SVM) to make the final decision. We train the Alexnet by using cracked regions and non-cracked regions to extract deep feature of cracked region. ![]() In this paper, we pay attention to localized cracked regions of the tongue instead of the whole tongue. ![]() ![]() The existing methods make use of handcraft features to classify the cracked tongue which leads to inconstant performance when the length or width of crack is various. ![]() However, due to similar model of real and fake tongue crack, cracked tongue recognition is still challenging. Cracked tongue can provide valuable diagnostic information for traditional Chinese Medicine doctors. ![]()
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