David J. Brady
Computational Mechanics · Optics Express · 2006–2021
A researcher in the Science corpus: 13 papers; trusts 111 researchers and is trusted by 21 researchers here, as inferred from the citation graph.
Subfields
- Computational Mechanics — 81 citations into it; #2,021 of 10,001 by trust here, #2,156 by citations
- Computer Vision and Pattern Recognition — 70 citations into it; #21,118 of 21,575 by trust here, #17,757 by citations
- Biomedical Engineering — 28 citations into it; #5,607 of 10,734 by trust here, #3,410 by citations
- Media Technology — 16 citations into it
- Radiology, Nuclear Medicine and Imaging — 15 citations into it; #1,948 of 3,265 by trust here, #2,195 by citations
- Signal Processing — 15 citations into it
- Applied Mathematics — 14 citations into it
- Electrical and Electronic Engineering — 13 citations into it; #14,278 of 16,539 by trust here, #11,313 by citations
Whom David J. Brady trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- E.J. Candes
- Mário A. T. Figueiredo
- Stéphane Mallat
- José M. Bioucas-Dias
- Ashwin A. Wagadarikar
- David L. Donoho
- Terence Tao
- Scott Shaobing Chen
- Renu John
- Robert D. Nowak
Who trusts David J. Brady overall
Papers from David J. Brady's perspective
Ordered by how strongly the researchers David J. Brady 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
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- GENERATIVE ADVERSARIAL NETS
- ImageNet: A large-scale hierarchical image database
- Regression Shrinkage and Selection via the Lasso
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Multiframe image estimation for coded aperture snapshot spectral imagers. (2010) — 321 citations
- Snapshot Compressive Imaging: Theory, Algorithms, and Applications (2021) — 332 citations
- Rank Minimization for Snapshot Compressive Imaging (2018) — 426 citations
- Single disperser design for coded aperture snapshot spectral imaging. (2008) — 962 citations
- Single-shot compressive spectral imaging with a dual-disperser architecture. (2007) — 753 citations
- Multiscale gigapixel photography (2012) — 320 citations
- Coded aperture compressive temporal imaging (2013) — 412 citations
- Metamaterial Apertures for Computational Imaging (2013) — 580 citations
- Compressive Coded Aperture Spectral Imaging: An Introduction (2014) — 567 citations
- Compressive holography. (2009) — 386 citations
- Optical Imaging and Spectroscopy (2009) — 143 citations
- Video rate spectral imaging using a coded aperture snapshot spectral imager. (2009) — 348 citations
- Human-tracking systems using pyroelectric infrared detectors (2006) — 155 citations