Ke Chen

Computer Vision and Pattern Recognition · Scientific Reports · 2004–2023

A researcher in the Science corpus: 16 papers; trusts 630 researchers and is trusted by 23 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 188 citations into it; #5,588 of 21,575 by trust here, #3,645 by citations
• Artificial Intelligence — 117 citations into it; #14,930 of 35,345 by trust here, #5,638 by citations
• Aerospace Engineering — 28 citations into it
• Evaluation & Benchmarks — 17 citations into it
• Generative Models — 15 citations into it
• Model Architectures — 13 citations into it
• Optimization & Training — 13 citations into it
• Representation & Self-Supervised Learning — 12 citations into it

Whom Ke Chen trusts overall

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

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

Who trusts Ke Chen overall

1. Vishwanath A. Sindagi
2. Vishal M. Patel
3. Haroon Idrees
4. Huidong Liu
5. M. Hsieh
6. Sergey I. Nikolenko
7. Viet Quoc Pham
8. Ning Liu
9. Aron Yu
10. Viresh Ranjan

Papers from Ke Chen's perspective

Ordered by how strongly the researchers Ke Chen 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. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
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

• Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic (2023) — 964 citations
• Structured Knowledge Distillation for Semantic Segmentation (2019) — 708 citations
• Cumulative Attribute Space for Age and Crowd Density Estimation (2013) — 451 citations
• Feature Mining for Localised Crowd Counting (2012) — 668 citations
• Point-Bind & Point-LLM: Aligning Point Cloud with Multi-modality for 3D Understanding, Generation, and Instruction Following (2023) — 235 citations
• A general Lewis acidic etching route for preparing MXenes with enhanced electrochemical performance in non-aqueous electrolyte (2019) — 1,277 citations
• CACTI-P: Architecture-level modeling for SRAM-based structures with advanced leakage reduction techniques (2011) — 298 citations
• Continual Federated Learning Based on Knowledge Distillation (2022) — 132 citations
• Uptake, distribution, clearance, and toxicity of iron oxide nanoparticles with different sizes and coatings (2018) — 597 citations
• CSCD: a database for cancer-specific circular RNAs (2017) — 346 citations
• Physiological change and nutritional requirement of Pacific white shrimpLitopenaeus vannameiat low salinity (2017) — 196 citations
• Dynamic control of electromagnetic wave propagation with the equivalent principle inspired tunable metasurface (2014) — 157 citations
• The knowing camera 2: recognizing and annotating places-of-interest in smartphone photos (2014) — 10 citations
• Growth and Lipid Metabolism of the Pacific White Shrimp Litopenaeus vannamei at Different Salinities (2014) — 117 citations
• Morphology of sporadic E layer retrieved from COSMIC GPS radio occultation measurements: Wind shear theory examination (2014) — 136 citations
• Exploiting Unlabeled Data in Content-Based Image Retrieval (2004) — 97 citations