Attila Reiss

Computer Vision and Pattern Recognition · 2012–2019

A researcher in the Science corpus: 4 papers; trusts 24 researchers and is trusted by 17 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 16 citations into it; #6,382 of 21,575 by trust here, #11,286 by citations
• Experimental and Cognitive Psychology — 13 citations into it
• Artificial Intelligence — 12 citations into it
• Biomedical Engineering — 10 citations into it; #1,149 of 10,734 by trust here, #5,494 by citations
• Cardiology and Cardiovascular Medicine — 8 citations into it
• Model Architectures — 6 citations into it

Whom Attila Reiss trusts overall

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

1. Karen Simonyan
2. Kaiming He
3. Sergey Ioffe
4. Maytal Saar-Tsechansky
5. Christian Szegedy
6. Stephen S. Intille
7. Zhilin Zhang
8. Tim van Kasteren
9. Mark A. Hall
10. Andrew Zisserman

Who trusts Attila Reiss overall

1. Sreenivasan Ramasamy Ramamurthy
2. Yu Guan
3. Francisco Javier Ordonez
4. Nidhi Dua
5. Nils Y. Hammerla
6. Thomas Plötz
7. Philip Schmidt
8. Yu-xin Zhang
9. Erich Schubert
10. Jorge Luis Reyes-Ortiz

Papers from Attila Reiss's perspective

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

Their papers

• Introducing a New Benchmarked Dataset for Activity Monitoring (2012) — 1,406 citations
• Creating and benchmarking a new dataset for physical activity monitoring (2012) — 300 citations
• Deep PPG: Large-Scale Heart Rate Estimation with Convolutional Neural Networks (2019) — 408 citations
• Introducing WESAD, a Multimodal Dataset for Wearable Stress and Affect Detection (2018) — 1,275 citations