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Check this page out, it describes how to develop apply triplet loss to a network: https://towardsdatascience.com/image-similarity-using-triplet-loss-3744c0f67973


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One could imagine using a segmentation network as a first step of processing. Then feeding an area corresponding to a bounding box of each segmented object to the classifier. Potentially that could yield an increase in performance in classifying objects in an image, but not without a cost of training time, sine suddenly there are two networks to train ...


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