Deniz Erdoğmuş

Computer Vision and Pattern Recognition · 2002–2018

A researcher in the Science corpus: 6 papers; trusts 116 researchers and is trusted by 21 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 37 citations into it; #17,827 of 21,575 by trust here, #15,529 by citations
• Artificial Intelligence — 16 citations into it; #6,468 of 35,345 by trust here, #13,760 by citations
• Model Architectures — 10 citations into it
• Radiology, Nuclear Medicine and Imaging — 10 citations into it
• Aerospace Engineering — 7 citations into it
• Information Theory — 7 citations into it
• Optimization & Training — 7 citations into it
• Statistics and Probability — 6 citations into it

Whom Deniz Erdoğmuş trusts overall

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

1. Claude E. Shannon
2. Bernard Walter Silverman
3. Gene H. Golub
4. John G. Proakis
5. Bernhard Schölkopf
6. Shun-ichi Amari
7. Geoffrey E. Hinton
8. Anthony J. Bell
9. Diederik P. Kingma
10. Teuvo Kohonen

Who trusts Deniz Erdoğmuş overall

1. José Carlos Príncipe
2. Weifeng Liu
3. Puskal P. Pokharel
4. M. Ren
5. Kari Torkkola
6. Ignacio Santamaría
7. Qichun Zhang
8. Katerina Hlaváčková-Schindler
9. Ran He
10. Jian-hang Zhang

Papers from Deniz Erdoğmuş's perspective

Ordered by how strongly the researchers Deniz Erdoğmuş 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Information Theoretic Learning (2005) — 851 citations
• The Future of Human-in-the-Loop Cyber-Physical Systems (2013) — 321 citations
• Real-time Deep Pose Estimation with Geodesic Loss for Image-to-Template Rigid Registration (2018) — 123 citations
• Tversky Loss Function for Image Segmentation Using 3D Fully Convolutional Deep Networks (2017) — 1,143 citations
• 14 FROM LINEAR ADAPTIVE FILTERING TO NONLINEAR INFORMATION PROCESSING (2006) — 34 citations
• An error-entropy minimization algorithm for supervised training of nonlinear adaptive systems (2002) — 358 citations