Nasser Kehtarnavaz

Computer Vision and Pattern Recognition · 2007–2020

A researcher in the Science corpus: 11 papers; trusts 1,144 researchers and is trusted by 29 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 443 citations into it; #4,123 of 21,575 by trust here, #3,982 by citations
• Artificial Intelligence — 129 citations into it; #24,180 of 35,345 by trust here, #34,213 by citations
• Human-Computer Interaction — 73 citations into it; #173 of 2,253 by trust here, #241 by citations
• Biomedical Engineering — 58 citations into it; #442 of 10,734 by trust here, #2,323 by citations
• 3D Vision & Pose — 41 citations into it
• Computational Mechanics — 39 citations into it
• Model Architectures — 28 citations into it
• Radiology, Nuclear Medicine and Imaging — 28 citations into it

Whom Nasser Kehtarnavaz trusts overall

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

1. Ivan Laptev
2. Cheng Chen
3. Kaiming He
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. Roozbeh Jafari
7. Ross B. Girshick
8. Yann LeCun
9. Yoshua Bengio
10. Diederik P. Kingma

Who trusts Nasser Kehtarnavaz overall

1. Roozbeh Jafari
2. Zehua Sun
3. Cheng Chen
4. Mengyuan Liu
5. Jun Liu
6. Neha Dawar
7. Pichao Wang
8. Yong Du
9. Yonghong Hou
10. Hong Liu

Papers from Nasser Kehtarnavaz's perspective

Ordered by how strongly the researchers Nasser Kehtarnavaz 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. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
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. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Image Segmentation Using Deep Learning: A Survey (2020) — 3,812 citations
• UTD-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and a wearable inertial sensor (2015) — 772 citations
• A Real-Time Human Action Recognition System Using Depth and Inertial Sensor Fusion (2016) — 159 citations
• Improving Human Action Recognition Using Fusion of Depth Camera and Inertial Sensors (2015) — 252 citations
• A survey of depth and inertial sensor fusion for human action recognition (2015) — 332 citations
• Fusion of Inertial and Depth Sensor Data for Robust Hand Gesture Recognition (2014) — 159 citations
• Fusion of depth, skeleton, and inertial data for human action recognition (2016) — 66 citations
• Deep Learning-based Human Pose Estimation: A Survey (2020) — 975 citations
• A Convolutional Neural Network-Based Sensor Fusion System for Monitoring Transition Movements in Healthcare Applications (2018) — 36 citations
• Real-time human action recognition based on depth motion maps (2013) — 312 citations
• Brain Functional Localization: A Survey of Image Registration Techniques (2007) — 306 citations