Bert Moons
Computer Vision and Pattern Recognition · 2016–2017
A researcher in the Science corpus: 3 papers; trusts 22 researchers and is trusted by 10 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 16 citations into it; #9,398 of 21,575 by trust here, #11,950 by citations
- Electrical and Electronic Engineering — 8 citations into it; #4,041 of 16,539 by trust here, #8,489 by citations
Whom Bert Moons trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Yann LeCun
- Geoffrey E. Hinton
- Ilya Sutskever
- Yoshua Bengio
- L. Eon Bottou
- Swagath Venkataramani
- Karen Simonyan
- Marian Verhelst
- Kaiming He
Who trusts Bert Moons overall
- Shimeng Yu
- M. Mohammadi
- Md Maruf Hossain Shuvo
- Shree Krishna Sharma
- Yu-hsin Chen
- Van-Tam Nguyen
- Renzo Andri
- Marian Verhelst
- Mart van Baalen
- Ala Al-Fuqaha
Papers from Bert Moons's perspective
Ordered by how strongly the researchers Bert Moons trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Going deeper with convolutions
Their papers
- 14.5 Envision: A 0.26-to-10TOPS/W subword-parallel dynamic-voltage-accuracy-frequency-scalable Convolutional Neural Network processor in 28nm FDSOI (2017) — 400 citations
- A 0.3–2.6 TOPS/W precision-scalable processor for real-time large-scale ConvNets (2016) — 155 citations
- Energy-efficient ConvNets through approximate computing (2016) — 105 citations