Search Results for author:
Found 2 papers, 2 papers with code
What Deep CNNs Benefit from Global Covariance Pooling: An Optimization Perspective
Recent works have demonstrated that global covariance pooling (GCP) has the ability to improve performance of deep convolutional neural networks (CNNs) on visual classification task.
ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks
By dissecting the channel attention module in SENet, we empirically show avoiding dimensionality reduction is important for learning channel attention, and appropriate cross-channel interaction can preserve performance while significantly decreasing model complexity.
Ranked #732 on
Image Classification
on ImageNet
Cannot find the paper you are looking for? You can
Submit a new open access paper.
