Dhiraj Joshi

Computer Vision and Pattern Recognition · 2002–2020

A researcher in the Science corpus: 6 papers; trusts 335 researchers and is trusted by 151 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 148 citations into it; #2,943 of 21,575 by trust here, #4,402 by citations
• Artificial Intelligence — 58 citations into it; #17,493 of 35,345 by trust here, #19,873 by citations
• Multimodal Learning — 55 citations into it
• Signal Processing — 45 citations into it
• Representation & Self-Supervised Learning — 36 citations into it
• Information Retrieval & Search — 10 citations into it; #365 of 1,022 by trust here, #267 by citations
• Natural Language Processing — 9 citations into it
• Evaluation & Benchmarks — 7 citations into it

Whom Dhiraj Joshi trusts overall

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

1. Geoffrey E. Hinton
2. Jitendra Malik
3. Kaiming He
4. Alex Krizhevsky
5. Diederik P. Kingma
6. James Ze Wang
7. Andrew Zisserman
8. Yoshua Bengio
9. Yann LeCun
10. Ross B. Girshick

Who trusts Dhiraj Joshi overall

1. Jun Wang
2. Christian Beecks
3. Tony Lindeberg
4. Antonio Torralba
5. Kalyanmoy Deb
6. Xiaoou Tang
7. Martin Solli
8. Mathias Eitz
9. Luca Marchesotti
10. Yiwen Luo

Papers from Dhiraj Joshi's perspective

Ordered by how strongly the researchers Dhiraj Joshi 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. ImageNet: A large-scale hierarchical image database
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
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

• Image retrieval: Ideas, influences, and trends of the new age (2008) — 3,871 citations
• Studying Aesthetics in Photographic Images Using a Computational Approach (2006) — 1,045 citations
• AVLnet: Learning Audio-Visual Language Representations from Instructional Videos (2020) — 148 citations
• A Computationally Efficient Evolutionary Algorithm for Real-Parameter Optimization (2002) — 653 citations
• Grounding Spoken Words in Unlabeled Video (2019) — 24 citations
• Reinforced Similarity Integration in Image-Rich Information Networks (2013) — 43 citations