Mohamed Hamed N. Taha

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 2 papers; trusts 38 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 20 citations into it
• Artificial Intelligence — 11 citations into it

Whom Mohamed Hamed N. Taha trusts overall

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

1. Ross B. Girshick
2. Kaiming He
3. Diederik P. Kingma
4. Geoffrey E. Hinton
5. David G. Lowe
6. Alex Krizhevsky
7. Shaoqing Ren
8. Jimmy Ba
9. X. Zhang
10. Yann LeCun

Papers from Mohamed Hamed N. Taha's perspective

Ordered by how strongly the researchers Mohamed Hamed N. Taha 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. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
6. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• A hybrid deep transfer learning model with machine learning methods for face mask detection in the era of the COVID-19 pandemic (2020) — 610 citations
• Fighting against COVID-19: A novel deep learning model based on YOLO-v2 with ResNet-50 for medical face mask detection (2020) — 412 citations