Jing-yu Yang

Computer Vision and Pattern Recognition · Pattern Recognition · 1993–2013

A researcher in the Science corpus: 10 papers; trusts 42 researchers and is trusted by 25 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 55 citations into it; #4,899 of 21,575 by trust here, #7,499 by citations
• Artificial Intelligence — 16 citations into it
• Media Technology — 10 citations into it; #763 of 3,621 by trust here, #1,423 by citations
• Analytical Chemistry — 8 citations into it
• Statistical Learning Theory — 8 citations into it
• Signal Processing — 5 citations into it; #4,186 of 7,572 by trust here, #5,086 by citations

Whom Jing-yu Yang trusts overall

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

1. Peter N. Belhumeur
2. Bernhard Schölkopf
3. Robert Desimone
4. Ming-Hsuan Yang
5. David G. Lowe
6. K. Müller
7. Bangalore S. Manjunath
8. Geoffrey E. Hinton
9. P. Jonathon Phillips
10. Alex Smola

Who trusts Jing-yu Yang overall

1. Meng Yang
2. Jian Yang
3. Lei Zhang
4. Shuicheng Yan
5. Weihong Deng
6. David Dapeng Zhang
7. Jieping Ye
8. Xudong Jiang
9. Peg Howland
10. Su-Jing Wang

Papers from Jing-yu Yang's perspective

Ordered by how strongly the researchers Jing-yu Yang 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Globally Maximizing, Locally Minimizing: Unsupervised Discriminant Projection with Applications to Face and Palm Biometrics (2007) — 381 citations
• Content-based image retrieval using color difference histogram (2013) — 531 citations
• A Two-Phase Test Sample Sparse Representation Method for Use With Face Recognition (2011) — 504 citations
• Two-dimensional discriminant transform for face recognition (2005) — 336 citations
• KPCA plus LDA: a complete kernel Fisher discriminant framework for feature extraction and recognition (2005) — 899 citations
• Two-dimensional PCA: a new approach to appearance-based face representation and recognition (2004) — 3,748 citations
• Why can LDA be performed in PCA transformed space? (2003) — 616 citations
• Feature fusion: parallel strategy vs. serial strategy (2003) — 450 citations
• Face recognition based on the uncorrelated discriminant transformation (2001) — 403 citations
• Algebraic feature extraction for image recognition based on an optimal discriminant criterion (1993)