Sridha Sridharan

Computer Vision and Pattern Recognition · 2001–2020

A researcher in the Science corpus: 6 papers; trusts 277 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 98 citations into it; #10,836 of 21,575 by trust here, #10,010 by citations
• Artificial Intelligence — 74 citations into it; #17,334 of 35,345 by trust here, #13,544 by citations
• Computational Mechanics — 30 citations into it
• Model Architectures — 25 citations into it
• Signal Processing — 21 citations into it
• Genetics — 7 citations into it
• Natural Language Processing — 7 citations into it
• Optimization & Training — 6 citations into it

Whom Sridha Sridharan trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Yoshua Bengio
4. Diederik P. Kingma
5. Kaiming He
6. Yann LeCun
7. Ronald J. Williams
8. Karen Simonyan
9. Ilya Sutskever
10. Douglas A. Reynolds

Who trusts Sridha Sridharan overall

1. Najim Dehak
2. Patrick Kenny
3. Sylvain Meignier
4. Vasileios Vasilakakis
5. Shi-Xiong Zhang
6. Pierre Ouellet
7. Vishwanath A. Sindagi
8. Réda Dehak
9. Victor S. Lempitsky
10. Sandro Cumani

Papers from Sridha Sridharan's perspective

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

Their papers

• Crowd Counting Using Multiple Local Features (2009) — 321 citations
• Soft + Hardwired Attention: An LSTM Framework for Human Trajectory Prediction and Abnormal Event Detection (2017) — 361 citations
• Deep Learning for Medical Anomaly Detection – A Survey (2020) — 426 citations
• Iris Recognition With Off-the-Shelf CNN Features: A Deep Learning Perspective (2018) — 306 citations
• Image2Mesh: A Learning Framework for Single Image 3D Reconstruction (2017) — 138 citations
• Feature warping for robust speaker verification (2001) — 784 citations