234 citations · 310 across the 9 of their papers we have counts for
10 papers
FenceNet: Fine-grained Footwork Recognition in Fencing
Kevin Zhu, Alexander Wong, John McPhee
Current data analysis for the Canadian Olympic fencing team is primarily done manually by coaches and analysts. Due to the highly repetitive, yet dynamic and subtle movements in fe…
Co-Optimization of On-Ramp Merging and Plug-In Hybrid Electric Vehicle Power Split Using Deep Reinforcement Learning
Yuan Lin, John McPhee, Nasser L. Azad
Current research on Deep Reinforcement Learning (DRL) for automated on-ramp merging neglects vehicle powertrain and dynamics. This work considers automated on-ramp merging for a po…
Rethinking Keypoint Representations: Modeling Keypoints and Poses as Objects for Multi-Person Human Pose Estimation
William McNally, Kanav Vats, Alexander Wong +1
In keypoint estimation tasks such as human pose estimation, heatmap-based regression is the dominant approach despite possessing notable drawbacks: heatmaps intrinsically suffer fr…
DeepDarts: Modeling Keypoints as Objects for Automatic Scorekeeping in Darts using a Single Camera
William McNally, Pascale Walters, Kanav Vats +2
Existing multi-camera solutions for automatic scorekeeping in steel-tip darts are very expensive and thus inaccessible to most players. Motivated to develop a more accessible low-c…
EvoPose2D: Pushing the Boundaries of 2D Human Pose Estimation using Accelerated Neuroevolution with Weight Transfer
William McNally, Kanav Vats, Alexander Wong +1
Neural architecture search has proven to be highly effective in the design of efficient convolutional neural networks that are better suited for mobile deployment than hand-designe…
Comparison of Deep Reinforcement Learning and Model Predictive Control for Adaptive Cruise Control
Yuan Lin, John McPhee, Nasser L. Azad
This study compares Deep Reinforcement Learning (DRL) and Model Predictive Control (MPC) for Adaptive Cruise Control (ACC) design in car-following scenarios. A first-order system i…