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Framework of the proposed method. It includes a pre-trained CNN module; an SRP module for generating tooth mark candidate regions; an SPP-layer for obtaining and normalizing the deep features of tooth mark candidate regions; two weakly supervised branches, a classification module and a detection module; The hadamard operation of the branch results and summation yields the image-level classification results.
