Mrigank Rochan

Computer Vision and Pattern Recognition · 2017–2019

A researcher in the Science corpus: 3 papers; trusts 535 researchers and is trusted by 19 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 47 citations into it; #7,166 of 21,575 by trust here, #8,021 by citations
• Artificial Intelligence — 26 citations into it; #13,642 of 35,345 by trust here, #18,586 by citations
• Model Architectures — 13 citations into it
• Natural Language Processing — 10 citations into it
• Multimodal Learning — 8 citations into it; #476 of 1,211 by trust here, #909 by citations
• Aerospace Engineering — 6 citations into it
• Computer Networks and Communications — 6 citations into it

Whom Mrigank Rochan trusts overall

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

1. Karen Simonyan
2. Geoffrey E. Hinton
3. Kaiming He
4. Diederik P. Kingma
5. Alex Krizhevsky
6. Yoshua Bengio
7. Ross B. Girshick
8. Andrew Zisserman
9. Yann LeCun
10. Ilya Sutskever

Who trusts Mrigank Rochan overall

1. Henghui Ding
2. Golnaz Ghiasi
3. Liang-Chieh Chen
4. Timo Lüddecke
5. Seonguk Seo
6. Dave Zhenyu Chen
7. Qingyun Fang
8. Mengyang Feng
9. Shaoxiang Chen
10. Arsha Nagrani

Papers from Mrigank Rochan's perspective

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

Their papers

• Gated Feedback Refinement Network for Dense Image Labeling (2017) — 210 citations
• Cross-Modal Self-Attention Network for Referring Image Segmentation (2019) — 588 citations
• Malware Classification with Deep Convolutional Neural Networks (2018) — 354 citations