Md Mostafijur Rahman

Computer Vision and Pattern Recognition · 2023–2024

A researcher in the Science corpus: 2 papers; trusts 464 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 71 citations into it; #17,720 of 21,575 by trust here, #21,424 by citations
• Artificial Intelligence — 31 citations into it; #28,857 of 35,345 by trust here, #34,943 by citations
• Model Architectures — 24 citations into it
• Radiology, Nuclear Medicine and Imaging — 18 citations into it
• Oncology — 13 citations into it
• Efficiency & Compression — 5 citations into it
• Media Technology — 5 citations into it
• Optimization & Training — 5 citations into it

Whom Md Mostafijur Rahman trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Geoffrey E. Hinton
4. Karen Simonyan
5. Wenhai Wang
6. Ilya Loshchilov
7. Ilya Sutskever
8. Ross B. Girshick
9. Yoshua Bengio
10. Christian Szegedy

Who trusts Md Mostafijur Rahman overall

1. Mustafa Munir
2. Radu Marculescu

Papers from Md Mostafijur Rahman's perspective

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

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

Their papers

• EMCAD: Efficient Multi-Scale Convolutional Attention Decoding for Medical Image Segmentation (2024) — 329 citations
• Medical Image Segmentation via Cascaded Attention Decoding (2023) — 333 citations