Alejandro González
Computer Vision and Pattern Recognition · 2015–2017
A researcher in the Science corpus: 3 papers; trusts 100 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 52 citations into it; #13,827 of 21,575 by trust here, #9,872 by citations
- Artificial Intelligence — 17 citations into it
- Aerospace Engineering — 8 citations into it
Whom Alejandro González trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Markus Enzweiler
- Navneet Dalal
- Piotr Doll'ar
- Pedro F. Felzenszwalb
- Ross B. Girshick
- Bastian Leibe
- Dariu M. Gavrila
- Bill Triggs
- Cristiano Premebida
- Xiaoyu Wang
Who trusts Alejandro González overall
- Andreas Pfeuffer
- Xiaodan Liang
- Yin Zhou
- Klaus C. J. Dietmayer
- Zetong Yang
- Xiaozhi Chen
- Haoxuan You
- Shengmei Shen
- Oncel Tuzel
- Gregory P. Meyer
Papers from Alejandro González's perspective
Ordered by how strongly the researchers Alejandro González trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet: A large-scale hierarchical image database
- 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)
- Long Short-Term Memory
- ImageNet Large Scale Visual Recognition Challenge
- Attention is All you Need (Neural Information Processing Systems)
- Going deeper with convolutions
Their papers
- Multiview random forest of local experts combining RGB and LIDAR data for pedestrian detection (2015) — 86 citations
- On-Board Object Detection: Multicue, Multimodal, and Multiview Random Forest of Local Experts (2017) — 103 citations
- Pedestrian Detection at Day/Night Time with Visible and FIR Cameras: A Comparison (2016) — 313 citations