José Neira
Computer Vision and Pattern Recognition · 1999–2020
A researcher in the Science corpus: 8 papers; trusts 88 researchers and is trusted by 57 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 115 citations into it; #16,696 of 21,575 by trust here, #10,905 by citations
- Aerospace Engineering — 114 citations into it; #214 of 6,421 by trust here, #441 by citations
- Geology — 26 citations into it
- Electrical and Electronic Engineering — 23 citations into it; #398 of 16,539 by trust here, #3,087 by citations
- Artificial Intelligence — 20 citations into it; #4,778 of 35,345 by trust here, #15,236 by citations
- Ocean Engineering — 11 citations into it; #1,067 of 3,193 by trust here, #1,136 by citations
- Computer Networks and Communications — 7 citations into it; #8,388 of 9,886 by trust here, #1,475 by citations
- Robotics & Control — 7 citations into it; #161 of 609 by trust here, #148 by citations
Whom José Neira trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- José A. Castellanos
- Juan D. Tardós
- José E. Guivant
- John J. Leonard
- Sebastian Thrun
- Eduardo Mario Nebot
- Tim Bailey
- José M. M. Montiel
- Benjamin Kuipers
- Raul Mur-Artal
Who trusts José Neira overall
- Tim Bailey
- Michael Kaess
- Paul M. Newman
- M. Bosse
- Giorgio Grisetti
- Juan D. Tardós
- Andrew J. Davison
- Sebastian Thrun
- Carlos Estrada
- H. F. Durrant-Whyte
Papers from José Neira's perspective
Ordered by how strongly the researchers José Neira 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)
- Distinctive Image Features from Scale-Invariant Keypoints
- ImageNet: A large-scale hierarchical image database
- Microsoft COCO: Common Objects in Context
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet Large Scale Visual Recognition Challenge
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Mapping Large Loops with a Single Hand-Held Camera (2007) — 305 citations
- DynaSLAM: Tracking, Mapping, and Inpainting in Dynamic Scenes (2018) — 1,214 citations
- Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age (2016) — 3,487 citations
- Data association in stochastic mapping using the joint compatibility test (2001) — 884 citations
- Robust Mapping and Localization in Indoor Environments Using Sonar Data (2002) — 619 citations
- DynaSLAM II: Tightly-Coupled Multi-Object Tracking and SLAM (2020) — 298 citations
- Hierarchical SLAM: real-time accurate mapping of large environments (2005) — 461 citations
- The SPmap: a probabilistic framework for simultaneous localization and map building (1999)