T. Clancy

Artificial Intelligence · IEEE Journal on Selected Topics in Signal Processing · 2007–2017

A researcher in the Science corpus: 5 papers; trusts 48 researchers and is trusted by 20 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 19 citations into it; #9,524 of 35,345 by trust here, #13,163 by citations
• Computer Networks and Communications — 18 citations into it; #6,505 of 9,886 by trust here, #6,217 by citations
• Computer Vision and Pattern Recognition — 12 citations into it; #7,420 of 21,575 by trust here, #12,419 by citations
• Electrical and Electronic Engineering — 11 citations into it; #13,823 of 16,539 by trust here, #14,379 by citations
• Model Architectures — 9 citations into it
• Optimization & Training — 8 citations into it
• Signal Processing — 6 citations into it; #1,804 of 7,572 by trust here, #2,221 by citations

Whom T. Clancy trusts overall

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

1. Geoffrey E. Hinton
2. Yann LeCun
3. Alex Krizhevsky
4. Diederik P. Kingma
5. Kaiming He
6. Yoshua Bengio
7. Tim O'Shea
8. Ruiliang Chen
9. Ilya Sutskever
10. Christian Szegedy

Who trusts T. Clancy overall

1. Mario Bkassiny
2. Paul de Kerret
3. Tim O'Shea
4. Meysam Sadeghi
5. Beibei Wang
6. S. Nawaz
7. Alexandros G. Fragkiadakis
8. Woongsup Lee
9. Mingzhe Chen
10. Yang Li

Papers from T. Clancy's perspective

Ordered by how strongly the researchers T. Clancy 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Going deeper with convolutions
7. Attention is All you Need (Neural Information Processing Systems)
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. ImageNet: A large-scale hierarchical image database
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Convolutional Radio Modulation Recognition Networks (2016) — 1,385 citations
• Security in Cognitive Radio Networks: Threats and Mitigation (2008) — 405 citations
• Over-the-Air Deep Learning Based Radio Signal Classification (2017) — 1,429 citations
• An anti-jamming stochastic game for cognitive radio networks (2011) — 294 citations
• Applications of Machine Learning to Cognitive Radio Networks (2007) — 339 citations