Aitor Alvarez-Gila

Computer Vision and Pattern Recognition · 2015–2020

A researcher in the Science corpus: 5 papers; trusts 45 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 57 citations into it; #12,979 of 21,575 by trust here, #12,172 by citations
• Artificial Intelligence — 30 citations into it
• Media Technology — 13 citations into it; #1,945 of 3,621 by trust here, #1,770 by citations
• Atomic and Molecular Physics, and Optics — 7 citations into it

Whom Aitor Alvarez-Gila trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. X. Zhang
4. Christian Szegedy
5. Geoffrey E. Hinton
6. Shaoqing Ren
7. Ross B. Girshick
8. Karen Simonyan
9. Yoav Y. Schechner
10. Yann LeCun

Who trusts Aitor Alvarez-Gila overall

1. Lili Li
2. Yan-Tsung Peng
3. Agnieszka Mikołajczyk
4. Chongyi Li

Papers from Aitor Alvarez-Gila's perspective

Ordered by how strongly the researchers Aitor Alvarez-Gila 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. Going deeper with convolutions
4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. ImageNet: A large-scale hierarchical image database
8. Long Short-Term Memory
9. Attention is All you Need (Neural Information Processing Systems)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Few-Shot Learning approach for plant disease classification using images taken in the field (2020) — 316 citations
• Deep convolutional neural networks for mobile capture device-based crop disease classification in the wild (2019) — 486 citations
• Automatic plant disease diagnosis using mobile capture devices, applied on a wheat use case (2017) — 360 citations
• Data-Driven Color Augmentation Techniques for Deep Skin Image Analysis (2017) — 68 citations
• Automatic Red-Channel underwater image restoration (2015) — 932 citations