Clothing pattern recognition on social media is a key application of Internet marketing, but it is currently implemented manually, which is very inefficient. Our goal is to solve this problem through artificial intelligence. Based on the improved Mask RCNN network, this paper introduces the attention mechanism SENet to enable the feature extractor to extract the target areas that need to be focused on. And put more weight on this part to highlight significant useful features. And this article contributes a whole new dataset of clothing versions. The comparison experiment verifies that the improved Mask RCNN network has been significantly improved in the pattern recognition of clothing.
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