Ty Nguyen
PhD, MEAM (on Leave of Absence)
Ty’s research interests are in the areas of Machine Learning, Robotics and Artificial Intelligence. His current focuses are on Control & Optimization, Deep Reinforcement Learning, Knowledge Transfer and Probabilistic Modeling. As a long-term goal, he whole-heartedly works to facilitate the coexisting of robots and intelligent agents with us.
Publications
Any Way You Look At It: Semantic Crossview Localization and Mapping with LiDAR
Publisher IEEE International Conference on Robotics and Automation (ICRA)
Depth completion via deep basis fitting
Publisher IEEE Winter Conference on Applications of Computer Vision (WACV)
Evaluating Robust, Perception Based Controllers with Quadrotors
Publisher IEEE International Conference on Intelligent Robots and Systems (IROS)
Publisher arXiv
Dfusenet: Deep fusion of rgb and sparse depth information for image guided dense depth completion
Publisher Institute of Electrical and Electronics Engineers (IEEE)
Mavnet: An effective semantic segmentation micro-network for mav-based tasks
Publisher Institute of Electrical and Electronics Engineers (IEEE)
Publisher arXiv
Publisher arXiv
Unsupervised Deep Homography: A Fast and Robust Homography Estimation Model
Publisher IEEE Robotics and Automation Letters (RA-L)