Thomas Defard

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 18 citations into it; #30,734 of 35,345 by trust here, #20,836 by citations
• Computer Vision and Pattern Recognition — 9 citations into it
• Computer Networks and Communications — 5 citations into it

Whom Thomas Defard trusts overall

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

1. Kaiming He
2. Sergey Zagoruyko
3. Niv Cohen
4. Paul Bergmann
5. Kimin Lee
6. X. Zhang
7. Alex Krizhevsky
8. Shaoqing Ren
9. Geoffrey E. Hinton
10. Nikos Komodakis

Who trusts Thomas Defard overall

1. Hanqiu Deng
2. Yang Zou
3. Jongheon Jeong
4. Kilian Batzner
5. Sungwook Lee
6. Vitjan Zavrtanik
7. Denis A. Gudovskiy
8. Zhikang Liu
9. Guodong Wang
10. Zhaopeng Gu

Papers from Thomas Defard's perspective

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

Their papers

• PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization (2020) — 1,422 citations