Yushi Jing

Computer Vision and Pattern Recognition · 2008–2017

A researcher in the Science corpus: 6 papers; trusts 558 researchers and is trusted by 40 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 94 citations into it; #4,610 of 21,575 by trust here, #6,542 by citations
• Artificial Intelligence — 54 citations into it
• Information Systems — 18 citations into it; #4,918 of 8,771 by trust here, #2,406 by citations
• Representation & Self-Supervised Learning — 17 citations into it
• Natural Language Processing — 15 citations into it
• Model Architectures — 13 citations into it
• Information Retrieval & Search — 11 citations into it
• Evaluation & Benchmarks — 10 citations into it

Whom Yushi Jing trusts overall

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

1. David G. Lowe
2. Rob Fergus
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Andrew Zisserman
6. Ilya Sutskever
7. Yoshua Bengio
8. Kaiming He
9. Karen Simonyan
10. Ross B. Girshick

Who trusts Yushi Jing overall

1. Do Hang Nga
2. Dmitry Kislyuk
3. Lingxi Xie
4. Xirong Li
5. Boon-Siew Seah
6. Rob Fergus
7. Sare Gul Sevil
8. Meng Wang
9. David C. Liu
10. Junjie Cai

Papers from Yushi Jing's perspective

Ordered by how strongly the researchers Yushi Jing trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
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. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. Going deeper with convolutions
9. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• VisualRank: Applying PageRank to Large-Scale Image Search (2008) — 499 citations
• Training and Evaluating Multimodal Word Embeddings with Large-scale Web Annotated Images (2016) — 51 citations
• Visual Discovery at Pinterest (2017) — 84 citations
• Video suggestion and discovery for youtube: taking random walks through the view graph (2008) — 521 citations
• Related Pins at Pinterest: The Evolution of a Real-World Recommender System (2017) — 139 citations
• Human Curation and Convnets: Powering Item-to-Item Recommendations on Pinterest (2015) — 13 citations