Can we encourage sparsity in feature maps during training?

Jul 11, 2021 ... Model compactness As a result of the use of different filter sizes with feature concatenation and skip connections at every stage, feature maps ... Jul 28, 2023 ... In CNNs, feature maps are the output produced after applying the convolution operation with different filters. Each feature map corresponds to a ... In this paper, we design a light CNN architecture that addresses these challenges. Specifically, we implemented Max-feature-map (MFM) into each convolutional ... Dec 15, 2016 ... How can i visualize feature map of 1D CNN? #4729 ... type:support User is asking for help / asking an implementation question. Stackoverflow would ... ter redundancy or feature map redundancy. Previously. CNN optimization works mainly targets static model pa- rameter redundancy removal including many ... Aug 18, 2018 ... After finishing the previous two steps, we're supposed to have a pooled feature map by now. As the name of this step implies, ... Feb 22, 2019 ... Specifically, the task involves identifying useful 2D-CNN input feature maps for enhancing speaker identification with an ultimate goal to ... a feature map of 13*13 will be obtained for images with the size of 416*416 ... Weld defect map recognition based on improved Faster R-CNN [J]. China ... For every proposed plane, the feature maps of the reference image are stacked on top of the war- ped feature map of the other image. This produces a cost ... A local feature CNN extracts the coarse-level feature maps F ~ A and F ~ ... feature map. Coarse matches will be refined within this local window to a sub ...