Joseph F. Murray

Computer Vision and Pattern Recognition · 2003–2010

A researcher in the Science corpus: 4 papers; trusts 17 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 28 citations into it; #10,473 of 21,575 by trust here, #6,542 by citations
• Artificial Intelligence — 9 citations into it; #34,930 of 35,345 by trust here, #15,236 by citations
• Neuroscience — 5 citations into it
• Statistics and Probability — 5 citations into it

Whom Joseph F. Murray trusts overall

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

1. Yann LeCun
2. C. Burges
3. Robert A. Lordo
4. David J. Field
5. Jun Wang
6. Barbara Olshausen
7. L. Eon Bottou
8. Yoshua Bengio
9. Geoffrey E. Hinton
10. Vladimir Naumovich Vapni

Who trusts Joseph F. Murray overall

1. Charles Bergeron
2. Viren Jain
3. Marc-Andre Carbonneau
4. Michal Aharon
5. Michael Elad
6. Jed Zaretzki
7. Seungjin Choi
8. Soo-Young Lee
9. Alfred Marcel Bruckstein
10. uriy Mishchenko

Papers from Joseph F. Murray's perspective

Ordered by how strongly the researchers Joseph F. Murray trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Supervised Learning of Image Restoration with Convolutional Networks (2007) — 253 citations
• Dictionary Learning Algorithms for Sparse Representation (2003) — 932 citations
• Convolutional Networks Can Learn to Generate Affinity Graphs for Image Segmentation (2010) — 408 citations
• Machine Learning Methods for Predicting Failures in Hard Drives: A Multiple-Instance Application (2005) — 305 citations