Haoyang Ye
Aerospace Engineering · 2019
A researcher in the Science corpus: 2 papers; trusts 16 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Aerospace Engineering — 20 citations into it; #2,691 of 6,421 by trust here, #4,570 by citations
- Computer Vision and Pattern Recognition — 12 citations into it
- Geology — 6 citations into it
- Electrical and Electronic Engineering — 5 citations into it; #5,972 of 16,539 by trust here, #12,727 by citations
Whom Haoyang Ye trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ji Zhang
- M. Bosse
- Tong Qin
- Jens Behley
- Raul Mur-Artal
- Eagle Jones
- Stefan Leutenegger
- Sanjiv Singh
- Morgan Quigley
- Peiliang Li
Who trusts Haoyang Ye overall
- Tixiao Shan
- Brendan Englot
- Wei Xu
- Mathias Gehrig
- Chao Qin
- Carlo Ratti
- Yixi Cai
- Daniela Rus
- Fu Zhang
- Willem Aarents
Papers from Haoyang Ye's perspective
Ordered by how strongly the researchers Haoyang Ye trusts endorse each paper. Same corpus, a different order for every researcher.
- Are we ready for autonomous driving? The KITTI vision benchmark suite
- LOAM: Lidar Odometry and Mapping in Real-time (Robotics: Science and Systems Conference)
- Keyframe-based visual–inertial odometry using nonlinear optimization
- Distinctive Image Features from Scale-Invariant Keypoints
- Efficient variants of the ICP algorithm (Proceedings Third International Conference on 3-D Digital Imaging and Modeling)
- Visual-inertial navigation, mapping and localization: A scalable real-time causal approach (Int. J. Robotics Res.)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Continuous 3D scan-matching with a spinning 2D laser (IEEE International Conference on Robotics and Automation)
- Visual-Inertial Monocular SLAM With Map Reuse (IEEE Robotics and Automation Letters)
Their papers
- Tightly Coupled 3D Lidar Inertial Odometry and Mapping (2019) — 506 citations
- LINS: A Lidar-Inertial State Estimator for Robust and Efficient Navigation (2019) — 334 citations