Adnan Qayyum

Artificial Intelligence · 2017–2021

A researcher in the Science corpus: 5 papers; trusts 183 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 195 citations into it; #25,058 of 35,345 by trust here, #20,377 by citations
• Computer Vision and Pattern Recognition — 102 citations into it; #19,540 of 21,575 by trust here, #16,787 by citations
• Safety, Robustness & Interpretability — 75 citations into it
• Radiology, Nuclear Medicine and Imaging — 58 citations into it
• Health Information Management — 23 citations into it
• Molecular Biology — 21 citations into it
• Biomedical Engineering — 12 citations into it
• Biophysics — 12 citations into it

Whom Adnan Qayyum trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Yoshua Bengio
4. Ilya Sutskever
5. Yann LeCun
6. Diederik P. Kingma
7. Kaiming He
8. Ruslan Salakhutdinov
9. Christian Szegedy
10. Ian J. Goodfellow

Who trusts Adnan Qayyum overall

1. Shiv Ram Dubey
2. Khansa Rasheed
3. Junaid Qadir
4. Ala Al-Fuqaha
5. Sweta Bhattacharya
6. Muhammad Bilal
7. Xuxin Chen
8. Arvid Lundervold
9. Mohamed Ghaly

Papers from Adnan Qayyum's perspective

Ordered by how strongly the researchers Adnan Qayyum 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. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
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. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Explainable, trustworthy, and ethical machine learning for healthcare: A survey (2021) — 320 citations
• Machine Learning for Predicting Epileptic Seizures Using EEG Signals: A Review (2020) — 323 citations
• Secure and Robust Machine Learning for Healthcare: A Survey (2020) — 471 citations
• Medical Image Analysis using Convolutional Neural Networks: A Review (2017) — 1,280 citations
• Medical image retrieval using deep convolutional neural network (2017) — 400 citations