Ahsan Iqbal

Computer Vision and Pattern Recognition · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 253 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 53 citations into it
• Artificial Intelligence — 27 citations into it
• Evaluation & Benchmarks — 8 citations into it
• Natural Language Processing — 7 citations into it
• Model Architectures — 6 citations into it
• Endocrinology, Diabetes and Metabolism — 5 citations into it
• Signal Processing — 5 citations into it

Whom Ahsan Iqbal trusts overall

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

1. Hilde Kuehne
2. Andrew Zisserman
3. Geoffrey E. Hinton
4. Karen Simonyan
5. Yoshua Bengio
6. Alex Krizhevsky
7. Kaiming He
8. Ivan Laptev
9. Alex Graves
10. Jia Deng

Papers from Ahsan Iqbal's perspective

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

Their papers

• Mining YouTube - A dataset for learning fine-grained action concepts from webly supervised video data (2019) — 18 citations
• NeuralNetwork-Viterbi: A Framework for Weakly Supervised Video Learning (2018) — 154 citations