Charles-Alban Deledalle
Computer Vision and Pattern Recognition · 2009–2019
A researcher in the Science corpus: 5 papers; trusts 77 researchers and is trusted by 10 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 93 citations into it; #10,111 of 21,575 by trust here, #15,955 by citations
- Signal Processing — 52 citations into it
- Computational Mechanics — 39 citations into it; #3,809 of 10,001 by trust here, #4,937 by citations
- Artificial Intelligence — 37 citations into it
- Media Technology — 32 citations into it; #1,828 of 3,621 by trust here, #2,954 by citations
- Statistics and Probability — 25 citations into it
- Optimization & Training — 24 citations into it
- Biomedical Engineering — 10 citations into it
Whom Charles-Alban Deledalle trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- A. Buades
- Patrick L. Combettes
- David L. Donoho
- Kostadin Dabov
- Alessandro Foi
- Bradley Efron
- Vladimir Katkovnik
- Carlo Tomasi
- Jörg Polzehl
- Bartomeu Coll
Who trusts Charles-Alban Deledalle overall
- Giovanni Chierchia
- Gabriele Steidl
- Xiaoxiang Zhu
- Puyang Wang
- Peter Ochs
- Fabian Pedregosa
- Fabrizio Argenti
- Sara Parrilli
- Davide Cozzolino
- Luisa Verdoliva
Papers from Charles-Alban Deledalle's perspective
Ordered by how strongly the researchers Charles-Alban Deledalle trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Machine learning in acoustics: Theory and applications. (2019) — 487 citations
- NL-SAR: A Unified Nonlocal Framework for Resolution-Preserving (Pol)(In)SAR Denoising (2015) — 415 citations
- Stein Unbiased GrAdient estimator of the Risk (SUGAR) for Multiple Parameter Selection (2014) — 125 citations
- Poisson Noise Reduction with Non-local PCA (2012) — 329 citations
- Iterative Weighted Maximum Likelihood Denoising With Probabilistic Patch-Based Weights (2009) — 802 citations