Mohammed A. Al-masni

Computer Vision and Pattern Recognition · 2018–2020

A researcher in the Science corpus: 3 papers; trusts 53 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 52 citations into it
• Artificial Intelligence — 49 citations into it
• Model Architectures — 11 citations into it
• Media Technology — 5 citations into it

Whom Mohammed A. Al-masni trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Ilya Sutskever
4. Karen Simonyan
5. Yoshua Bengio
6. Kaiming He
7. Christian Szegedy
8. Yann LeCun
9. Evan Shelhamer
10. Diederik P. Kingma

Who trusts Mohammed A. Al-masni overall

1. Yundong Zhang
2. Huiye Liu

Papers from Mohammed A. Al-masni's perspective

Ordered by how strongly the researchers Mohammed A. Al-masni 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. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Multiple skin lesions diagnostics via integrated deep convolutional networks for segmentation and classification (2020) — 328 citations
• A fully integrated computer-aided diagnosis system for digital X-ray mammograms via deep learning detection, segmentation, and classification (2018) — 354 citations
• Skin lesion segmentation in dermoscopy images via deep full resolution convolutional networks (2018) — 428 citations