Osama M. Abo-Seida

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 10 citations into it

Whom Osama M. Abo-Seida trusts overall

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

1. Karen Simonyan
2. Kaiming He

Papers from Osama M. Abo-Seida's perspective

Ordered by how strongly the researchers Osama M. Abo-Seida 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
4. Rethinking the Inception Architecture for Computer Vision
5. On the importance of initialization and momentum in deep learning
6. Gradient-based learning applied to document recognition
7. Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
8. Long Short-Term Memory
9. ImageNet Large Scale Visual Recognition Challenge
10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers

• A Novel Deep-Learning Model for Automatic Detection and Classification of Breast Cancer Using the Transfer-Learning Technique (2021) — 326 citations