6 citations · 7 across the 3 of their papers we have counts for
4 papers
PyFlyt -- UAV Simulation Environments for Reinforcement Learning Research
Jun Jet Tai, Jim Wong, Mauro Innocente +3
Unmanned aerial vehicles (UAVs) have numerous applications, but their efficient and optimal flight can be a challenge. Reinforcement Learning (RL) has emerged as a promising approa…
Some Supervision Required: Incorporating Oracle Policies in Reinforcement Learning via Epistemic Uncertainty Metrics
Jun Jet Tai, Jordan K. Terry, Mauro S. Innocente +2
An inherent problem of reinforcement learning is performing exploration of an environment through random actions, of which a large portion can be unproductive. Instead, exploration…
FasteNet: A Fast Railway Fastener Detector
Jun Jet Tai, Mauro S. Innocente, Owais Mehmood
In this work, a novel high-speed railway fastener detector is introduced. This fully convolutional network, dubbed FasteNet, foregoes the notion of bounding boxes and performs dete…
BOBBY2: Buffer Based Robust High-Speed Object Tracking
Keifer Lee, Jun Jet Tai, Swee King Phang
In this work, a novel high-speed single object tracker that is robust against non-semantic distractor exemplars is introduced; dubbed BOBBY2. It incorporates a novel exemplar buffe…