Aitor Aldoma
Computer Vision and Pattern Recognition · 2011–2012
A researcher in the Science corpus: 5 papers; trusts 58 researchers and is trusted by 24 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 45 citations into it; #6,273 of 21,575 by trust here, #9,079 by citations
- Aerospace Engineering — 34 citations into it; #870 of 6,421 by trust here, #1,425 by citations
- Geology — 17 citations into it; #207 of 687 by trust here, #267 by citations
- Computational Mechanics — 15 citations into it
- 3D Vision & Pose — 9 citations into it
- Artificial Intelligence — 7 citations into it
- Evaluation & Benchmarks — 6 citations into it
- Control and Systems Engineering — 5 citations into it; #6,323 of 8,257 by trust here, #7,831 by citations
Whom Aitor Aldoma trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Radu Bogdan Rusu
- Marius Muja
- Andrew E. Johnson
- David G. Lowe
- Federico Tombari
- Hui Chen
- Corey Goldfeder
- Gary R. Bradski
- Prabin Bariya
- Martial Hebert
Who trusts Aitor Aldoma overall
- Yulan Guo
- Samuele Salti
- Federico Tombari
- Alessio Tonioni
- Min Lu
- Ziyun Cai
- Marcus Gualtieri
- Hema Swetha Koppula
- Andreas ten Pas
- Jeffrey Mahler
Papers from Aitor Aldoma's perspective
Ordered by how strongly the researchers Aitor Aldoma trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet: A large-scale hierarchical image database
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Distinctive Image Features from Scale-Invariant Keypoints
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- A Global Hypotheses Verification Method for 3D Object Recognition (2012) — 187 citations
- 3DNet: Large-scale object class recognition from CAD models (2012) — 178 citations
- CAD-model recognition and 6DOF pose estimation using 3D cues (2011) — 335 citations
- Supervised learning of hidden and non-hidden 0-order affordances and detection in real scenes (2012) — 41 citations
- Tutorial: Point Cloud Library: Three-Dimensional Object Recognition and 6 DOF Pose Estimation (2012) — 385 citations