Saiprasad Ravishankar

Computational Mechanics · 2009–2013

A researcher in the Science corpus: 3 papers; trusts 34 researchers and is trusted by 18 researchers here, as inferred from the citation graph.

Subfields

• Computational Mechanics — 37 citations into it; #2,051 of 10,001 by trust here, #3,763 by citations
• Computer Vision and Pattern Recognition — 22 citations into it
• Radiology, Nuclear Medicine and Imaging — 13 citations into it; #360 of 3,265 by trust here, #1,628 by citations
• Signal Processing — 11 citations into it
• Media Technology — 6 citations into it
• Mechanics of Materials — 5 citations into it

Whom Saiprasad Ravishankar trusts overall

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

1. Michael Elad
2. David L. Donoho
3. Joel A. Tropp
4. Rick Chartrand
5. E.J. Candes
6. Barbara Olshausen
7. Michal Aharon
8. Julien Mairal
9. Ron Rubinstein
10. Michael Lustig

Who trusts Saiprasad Ravishankar overall

1. Yan Yang
2. Jo Schlemper
3. Tran Minh Quan
4. Ricardo Otazo
5. Bálint Antal
6. Huibin Li
7. Chen Qin
8. Taejoon Eo
9. Qiong Xu
10. Qingkai Kong

Papers from Saiprasad Ravishankar's perspective

Ordered by how strongly the researchers Saiprasad Ravishankar 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
6. ImageNet: A large-scale hierarchical image database
7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
8. ImageNet Large Scale Visual Recognition Challenge
9. Learning Multiple Layers of Features from Tiny Images
10. GENERATIVE ADVERSARIAL NETS

Their papers

• MR Image Reconstruction From Highly Undersampled k-Space Data by Dictionary Learning (2011) — 1,069 citations
• Learning Sparsifying Transforms (2013) — 354 citations
• Automated feature extraction for early detection of diabetic retinopathy in fundus images (2009) — 324 citations