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In order to further improve the feature extraction performance of the convolutional neural networks, we focus on the selection and reorganization of key features and suspect that simple changes in the pooling layers can cause changes in the performance of neural networks. According to the conjecture, we design a funnel convolution module, which can filter out the key features and perform multi-scale convolution of key features. And we apply this module to the design of high performance smalldoi:10.25046/aj050143 fatcat:6nftp2lr45e27m7pg5qp4gop6y