Steven K. Esser

Computer Vision and Pattern Recognition · 2009–2019

A researcher in the Science corpus: 8 papers; trusts 94 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 79 citations into it; #13,224 of 21,575 by trust here, #7,852 by citations
• Artificial Intelligence — 55 citations into it; #21,235 of 35,345 by trust here, #6,848 by citations
• Efficiency & Compression — 23 citations into it; #740 of 1,264 by trust here, #405 by citations
• Optimization & Training — 23 citations into it

Whom Steven K. Esser trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Alex Krizhevsky
4. Yann LeCun
5. Kaiming He
6. Ilya Sutskever
7. Matthieu Courbariaux
8. Diederik P. Kingma
9. Ilya Loshchilov
10. Ruslan Salakhutdinov

Who trusts Steven K. Esser overall

1. Sumit Bam Shrestha
2. Shimeng Yu
3. Markus Nagel
4. Yuhang Li
5. El Mahdi El Mhamdi
6. Md Maruf Hossain Shuvo
7. Bodo Rueckauer
8. Yelysei Bondarenko
9. Garrick Orchard
10. Tijmen Blankevoort

Papers from Steven K. Esser's perspective

Ordered by how strongly the researchers Steven K. Esser 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. Learning Multiple Layers of Features from Tiny Images
8. ImageNet: A large-scale hierarchical image database
9. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Learned Step Size Quantization (2019) — 1,090 citations
• Deep neural networks are robust to weight binarization and other non-linear distortions (2016) — 97 citations
• Convolutional networks for fast, energy-efficient neuromorphic computing (2016) — 763 citations
• A million spiking-neuron integrated circuit with a scalable communication network and interface (2014) — 3,922 citations
• A Low Power, Fully Event-Based Gesture Recognition System (2017) — 1,089 citations
• A 45nm CMOS neuromorphic chip with a scalable architecture for learning in networks of spiking neurons (2011) — 313 citations
• Backpropagation for Energy-Efficient Neuromorphic Computing (2015) — 328 citations
• The cat is out of the bag: cortical simulations with 109 neurons, 1013 synapses (2009) — 302 citations