Bogdan Georgescu

Computer Vision and Pattern Recognition · 2001–2019

A researcher in the Science corpus: 10 papers; trusts 168 researchers and is trusted by 121 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 78 citations into it; #3,063 of 21,575 by trust here, #5,236 by citations
• Artificial Intelligence — 37 citations into it
• Reinforcement Learning — 10 citations into it
• Optimization & Training — 9 citations into it
• Media Technology — 5 citations into it; #1,124 of 3,621 by trust here, #2,706 by citations
• Representation & Self-Supervised Learning — 5 citations into it

Whom Bogdan Georgescu trusts overall

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

1. Yoshua Bengio
2. Cordelia Schmid
3. Radford M. Neal
4. Geoffrey E. Hinton
5. Yann LeCun
6. Dorin Comaniciu
7. Alex Krizhevsky
8. Kaiming He
9. Jitendra Malik
10. Andrew Zisserman

Who trusts Bogdan Georgescu overall

1. Doug L. James
2. Carl Doersch
3. Oncel Tuzel
4. Gregory Shakhnarovich
5. Prateek Jain
6. Mathias Eitz
7. Li Liu
8. Damini Dey
9. Tao Chen
10. M. Sofka

Papers from Bogdan Georgescu's perspective

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

Their papers

• Mean shift based clustering in high dimensions: a texture classification example (2003) — 500 citations
• Edge Detection with Embedded Confidence (2001) — 447 citations
• Synergism in low level vision (2002) — 506 citations
• Combo Loss: Handling Input and Output Imbalance in Multi-Organ Segmentation (2018) — 434 citations
• An Artificial Agent for Anatomical Landmark Detection in Medical Images (2016) — 149 citations
• Multi-Scale Deep Reinforcement Learning for Real-Time 3D-Landmark Detection in CT Scans (2019) — 299 citations
• Four-Chamber Heart Modeling and Automatic Segmentation for 3-D Cardiac CT Volumes Using Marginal Space Learning and Steerable Features (2008) — 622 citations
• Towards intelligent robust detection of anatomical structures in incomplete volumetric data (2018) — 37 citations
• Nonlinear Adaptively Learned Optimization for Object Localization in 3D Medical Images (2018) — 3 citations
• A machine-learning approach for computation of fractional flow reserve from coronary computed tomography. (2016) — 380 citations