Md. Amirul Islam

Computer Vision and Pattern Recognition · with Bruce · 2017–2021

A researcher in the Science corpus: 4 papers; trusts 555 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 95 citations into it; #13,161 of 21,575 by trust here, #6,485 by citations
• Artificial Intelligence — 48 citations into it
• Model Architectures — 23 citations into it; #1,881 of 2,278 by trust here, #1,317 by citations
• Safety, Robustness & Interpretability — 13 citations into it; #1,855 of 2,251 by trust here, #1,265 by citations
• Cognitive Neuroscience — 9 citations into it
• Aerospace Engineering — 7 citations into it
• Biophysics — 6 citations into it
• Optimization & Training — 5 citations into it

Whom Md. Amirul Islam trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Karen Simonyan
5. Yoshua Bengio
6. Ross B. Girshick
7. Shaoqing Ren
8. Andrew Zisserman
9. Yann LeCun
10. Diederik P. Kingma

Who trusts Md. Amirul Islam overall

1. Daiqi Shi
2. Liang-Chieh Chen
3. Enze Xie
4. Xiaohong Huang
5. Mengyang Feng
6. Yuda Song
7. Sen Yang
8. Golnaz Ghiasi
9. Chieh Hubert Lin
10. Wenhai Wang

Papers from Md. Amirul Islam's perspective

Ordered by how strongly the researchers Md. Amirul Islam trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Gated Feedback Refinement Network for Dense Image Labeling (2017) — 210 citations
• How Much Position Information Do Convolutional Neural Networks Encode? (2020) — 408 citations
• Shape or Texture: Understanding Discriminative Features in CNNs (2021) — 93 citations
• Global Pooling, More than Meets the Eye: Position Information is Encoded Channel-Wise in CNNs (2021) — 36 citations