68 citations · 74 across the 5 of their papers we have counts for
10 papers
COVID-Net S: Towards computer-aided severity assessment via training and validation of deep neural networks for geographic extent and opacity extent scoring of chest X-rays for SARS-CoV-2 lung disease severity
Alexander Wong, Zhong Qiu Lin, Linda Wang +5
Background: A critical step in effective care and treatment planning for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of the COVID-19 pandemic, is the as…
COVID-Net: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest X-Ray Images
Linda Wang, Alexander Wong
The COVID-19 pandemic continues to have a devastating effect on the health and well-being of the global population. A critical step in the fight against COVID-19 is effective scree…
PuckNet: Estimating hockey puck location from broadcast video
Kanav Vats, William McNally, Chris Dulhanty +3
Puck location in ice hockey is essential for hockey analysts for determining the location of play and analyzing game events. However, because of the difficulty involved in obtainin…
Do Explanations Reflect Decisions? A Machine-centric Strategy to Quantify the Performance of Explainability Algorithms
Zhong Qiu Lin, Mohammad Javad Shafiee, Stanislav Bochkarev +3
There has been a significant surge of interest recently around the concept of explainable artificial intelligence (XAI), where the goal is to produce an interpretation for a decisi…
State of Compact Architecture Search For Deep Neural Networks
Mohammad Javad Shafiee, Andrew Hryniowski, Francis Li +2
The design of compact deep neural networks is a crucial task to enable widespread adoption of deep neural networks in the real-world, particularly for edge and mobile scenarios. Du…
Squeeze-and-Attention Networks for Semantic Segmentation
Zilong Zhong, Zhong Qiu Lin, Rene Bidart +6
The recent integration of attention mechanisms into segmentation networks improves their representational capabilities through a great emphasis on more informative features. Howeve…