activity
20172020
most citedFeedback Techniques in Computer-Based Simulation Training: A Survey

2 citations · 5 across the 4 of their papers we have counts for

collaborators

5 papers

cs.DB2020

Segmented Pairwise Distance for Time Series with Large Discontinuities

Jiabo He, Sarah Erfani, Sudanthi Wijewickrema +2

Time series with large discontinuities are common in many scenarios. However, existing distance-based algorithms (e.g., DTW and its derivative algorithms) may perform poorly in mea…

eess.IV20201 cited

Learning Non-Unique Segmentation with Reward-Penalty Dice Loss

Jiabo He, Sarah Erfani, Sudanthi Wijewickrema +2

Semantic segmentation is one of the key problems in the field of computer vision, as it enables computer image understanding. However, most research and applications of semantic se…

cs.CV2018

Dimensionality-Driven Learning with Noisy Labels

Xingjun Ma, Yisen Wang, Michael E. Houle +5

Datasets with significant proportions of noisy (incorrect) class labels present challenges for training accurate Deep Neural Networks (DNNs). We propose a new perspective for under…

cs.AI20172 cited

Providing Effective Real-time Feedback in Simulation-based Surgical Training

Xingjun Ma, Sudanthi Wijewickrema, Yun Zhou +3

Virtual reality simulation is becoming popular as a training platform in surgical education. However, one important aspect of simulation-based surgical training that has not receiv…

cs.HC20172 cited

Feedback Techniques in Computer-Based Simulation Training: A Survey

Sudanthi Wijewickrema, Xingjun Ma, James Bailey +2

Computer-based simulation training (CBST) is gaining popularity in a vast range of applications such as surgery, rehabilitation therapy, military applications, and driver/pilot tra…