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Found 4 papers, 2 papers with code
An Efficient Speech Separation Network Based on Recurrent Fusion Dilated Convolution and Channel Attention
We present an efficient speech separation neural network, ARFDCN, which combines dilated convolutions, multi-scale fusion (MSF), and channel attention to overcome the limited receptive field of convolution-based networks and the high computational cost of transformer-based networks.
Efficient Encoder-Decoder and Dual-Path Conformer for Comprehensive Feature Learning in Speech Enhancement
Current speech enhancement (SE) research has largely neglected channel attention and spatial attention, and encoder-decoder architecture-based networks have not adequately considered how to provide efficient inputs to the intermediate enhancement layer.
A Range-Null Space Decomposition Approach for Fast and Flexible Spectral Compressive Imaging
We present RND-SCI, a novel framework for compressive hyperspectral image (HSI) reconstruction.
A Simple Adaptive Unfolding Network for Hyperspectral Image Reconstruction
We present a simple, efficient, and scalable unfolding network, SAUNet, to simplify the network design with an adaptive alternate optimization framework for hyperspectral image (HSI) reconstruction.
