Search Results for author:
Found 2 papers, 1 papers with code
Weight Pruning via Adaptive Sparsity Loss
Pruning neural networks has regained interest in recent years as a means to compress state-of-the-art deep neural networks and enable their deployment on resource-constrained devices.
RecNets: Channel-wise Recurrent Convolutional Neural Networks
In this paper, we introduce Channel-wise recurrent convolutional neural networks (RecNets), a family of novel, compact neural network architectures for computer vision tasks inspired by recurrent neural networks (RNNs).
Cannot find the paper you are looking for? You can
Submit a new open access paper.
