C. De Vleeschouwer
Computer Vision and Pattern Recognition · 2003–2018
A researcher in the Science corpus: 5 papers; trusts 208 researchers and is trusted by 23 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 104 citations into it; #5,462 of 21,575 by trust here, #8,021 by citations
- Media Technology — 63 citations into it; #3,576 of 3,621 by trust here, #2,280 by citations
- Atomic and Molecular Physics, and Optics — 14 citations into it
- Computer Graphics and Computer-Aided Design — 7 citations into it; #502 of 1,584 by trust here, #976 by citations
- Evaluation & Benchmarks — 7 citations into it
Whom C. De Vleeschouwer trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Raanan Fattal
- Zhou Wang
- A. Bovik
- Kaiming He
- Srinivasa G. Narasimhan
- Cosmin Ancuți
- Jean-Philippe Tarel
- Codruta Orniana Ancuti
- Mohinder Malhotra
- Anish Mittal
Who trusts C. De Vleeschouwer overall
- Wei-Liang Tai
- Codruta Orniana Ancuti
- Diljith M. Thodi
- Lute Kamstra
- Chia-Chen Lin
- Yongjian Hu
- Dinu Coltuc
- Hyoung-Joong Kim
- Deniz Engin
- Cosmin Ancuți
Papers from C. De Vleeschouwer's perspective
Ordered by how strongly the researchers C. De Vleeschouwer 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Attention is All you Need (Neural Information Processing Systems)
- Going deeper with convolutions
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- O-HAZE: A Dehazing Benchmark with Real Hazy and Haze-Free Outdoor Images (2018) — 704 citations
- I-HAZE: a dehazing benchmark with real hazy and haze-free indoor images (2018) — 465 citations
- Color Balance and Fusion for Underwater Image Enhancement (2018) — 1,171 citations
- D-HAZY: A dataset to evaluate quantitatively dehazing algorithms (2016) — 338 citations
- Circular interpretation of bijective transformations in lossless watermarking for media asset management (2003) — 463 citations