Saman Kumara Halgamuge

Computer Vision and Pattern Recognition · 2000–2018

A researcher in the Science corpus: 4 papers; trusts 150 researchers and is trusted by 29 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 28 citations into it; #12,913 of 21,575 by trust here, #13,542 by citations
• Artificial Intelligence — 26 citations into it; #6,947 of 35,345 by trust here, #10,065 by citations
• Generative Models — 20 citations into it; #1,534 of 1,956 by trust here, #1,681 by citations
• Optimization & Training — 8 citations into it; #2,129 of 2,601 by trust here, #2,112 by citations
• Computational Theory and Mathematics — 5 citations into it
• Media Technology — 5 citations into it
• Model Architectures — 5 citations into it
• Statistical and Nonlinear Physics — 5 citations into it

Whom Saman Kumara Halgamuge trusts overall

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

1. R. Eberhart
2. Alex Krizhevsky
3. Diederik P. Kingma
4. Yuhui Shi
5. Geoffrey E. Hinton
6. Kaiming He
7. Christian Szegedy
8. Yoshua Bengio
9. Sergey Ioffe
10. Ian J. Goodfellow

Who trusts Saman Kumara Halgamuge overall

1. Zhi-hui Zhan
2. Zahra Beheshti
3. Jun Zhang
4. Weifeng Gao
5. Mohammad Reza Bonyadi
6. Pinar Çivicioglu
7. Hao Gao
8. Upuli Gunasinghe
9. Swagatam Das
10. Praveen Kumar Tripathi

Papers from Saman Kumara Halgamuge's perspective

Ordered by how strongly the researchers Saman Kumara Halgamuge 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. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Learning Multiple Layers of Features from Tiny Images
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Improving MMD-GAN Training with Repulsive Loss Function (2018) — 84 citations
• CONTRA: copy number analysis for targeted resequencing (2012) — 344 citations
• Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients (2004) — 3,011 citations
• Dynamic self-organizing maps with controlled growth for knowledge discovery (2000) — 564 citations