Javier Galbally

Computer Vision and Pattern Recognition · 2010–2014

A researcher in the Science corpus: 4 papers; trusts 56 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 58 citations into it; #8,524 of 21,575 by trust here, #9,872 by citations
• Signal Processing — 54 citations into it; #2,143 of 7,572 by trust here, #1,904 by citations
• Information Systems — 30 citations into it; #4,668 of 8,771 by trust here, #3,098 by citations
• Media Technology — 9 citations into it
• Genetics — 8 citations into it
• Safety Research — 5 citations into it

Whom Javier Galbally trusts overall

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

1. André Anjos
2. Eric R. Ziegel
3. Sébastien Marcel
4. Anil K. Jain
5. A. Bovik
6. Hamid R. Sheikh
7. Nesli Erdogmus
8. Ivana Chingovska
9. Jukka Määttä
10. Ismail Avcibas

Who trusts Javier Galbally overall

1. Ramachandra Raghavendra
2. Christoph Busch
3. Keyurkumar Patel
4. Rubén Tolosana
5. Battista Biggio
6. K. Raja
7. Yunpei Jia
8. Daniel Pérez-Cabo
9. Hu Han
10. Sébastien Marcel

Papers from Javier Galbally's perspective

Ordered by how strongly the researchers Javier Galbally 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Histograms of oriented gradients for human detection
6. Gradient-based learning applied to document recognition
7. Going deeper with convolutions
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

• Image Quality Assessment for Fake Biometric Detection: Application to Iris, Fingerprint, and Face Recognition (2014) — 605 citations
• Biometric Antispoofing Methods: A Survey in Face Recognition (2014) — 418 citations
• An evaluation of indirect attacks and countermeasures in fingerprint verification systems (2011) — 53 citations
• On the vulnerability of face verification systems to hill-climbing attacks (2010) — 148 citations