Dynamic Channel and Layer Gating in Convolutional Neural Networks

By Ali Ehteshami Bejnordi, Ralf Krestel. 2020

11 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Model Architectures, Efficiency & Compression

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Shiji Song
2. Yulin Wang
3. Gao Huang
4. Le Yang
5. Yizeng Han
6. Honghui Wang
7. Quoc V. Le
8. Alan L. Yuille

In Computer Vision and Pattern Recognition

1. Shiji Song
2. Yulin Wang
3. Gao Huang
4. Yizeng Han
5. Le Yang
6. Honghui Wang
7. Luc Van Gool
8. Alan L. Yuille

In Model Architectures

1. Shiji Song
2. Yulin Wang
3. Gao Huang
4. Honghui Wang
5. Le Yang
6. Yizeng Han
7. Quoc V. Le
8. Alan L. Yuille

In Efficiency & Compression

1. Shiji Song
2. Gao Huang
3. Yulin Wang
4. Le Yang
5. Yizeng Han
6. Honghui Wang

Citations in the corpus

• Dynamic Neural Networks: A Survey (2021, background): “On basis of the existing literature on dynamically skipping either network layers [47], [48] or convolutional filters [15], [85], [86], [87], recent work [92], [93], [94] has realized dynamic inference with respect to network depth and width simultaneously: only if a layer is determined to be execut”