Lianwen Jin

Computer Vision and Pattern Recognition · 2009–2020

A researcher in the Science corpus: 12 papers; trusts 938 researchers and is trusted by 38 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 257 citations into it; #4,417 of 21,575 by trust here, #5,620 by citations
• Artificial Intelligence — 77 citations into it; #14,798 of 35,345 by trust here, #18,586 by citations
• Media Technology — 62 citations into it; #3,035 of 3,621 by trust here, #1,646 by citations
• Natural Language Processing — 41 citations into it
• Model Architectures — 31 citations into it
• Aerospace Engineering — 15 citations into it
• Optimization & Training — 12 citations into it
• Signal Processing — 12 citations into it

Whom Lianwen Jin trusts overall

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

1. Kaiming He
2. Ross B. Girshick
3. Karen Simonyan
4. Geoffrey E. Hinton
5. Andrew Zisserman
6. Alex Krizhevsky
7. Yoshua Bengio
8. Yann LeCun
9. Shaoqing Ren
10. David G. Lowe

Who trusts Lianwen Jin overall

1. Minghui Liao
2. Yixing Zhu
3. Yuliang Liu
4. Shangbang Long
5. Xiaobing Wang
6. Yuqing Chen
7. Oscar D. Lara
8. Jun Du
9. Cong Yao
10. Xiang Bai

Papers from Lianwen Jin's perspective

Ordered by how strongly the researchers Lianwen Jin 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. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
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

• On the General Value of Evidence, and Bilingual Scene-Text Visual Question Answering (2020) — 128 citations
• Curved scene text detection via transverse and longitudinal sequence connection (2019) — 307 citations
• Detecting Curve Text in the Wild: New Dataset and New Solution (2017) — 295 citations
• Multi-Task Deep Reinforcement Learning for Continuous Action Control (2017) — 68 citations
• Decoupled Attention Network for Text Recognition (2019) — 294 citations
• High performance offline handwritten Chinese character recognition using GoogLeNet and directional feature maps (2015) — 306 citations
• Activity recognition from acceleration data based on discrete consine transform and SVM (2009) — 304 citations
• ABCNet: Real-Time Scene Text Spotting With Adaptive Bezier-Curve Network (2020) — 402 citations
• A Multi-Object Rectified Attention Network for Scene Text Recognition (2019) — 307 citations
• Deep Matching Prior Network: Toward Tighter Multi-oriented Text Detection (2017) — 322 citations
• Rank Preserving Sparse Learning for Kinect Based Scene Classification (2013) — 48 citations
• A novel feature extraction method using Pyramid Histogram of Orientation Gradients for smile recognition (2009) — 163 citations