3 citations · 10 across the 5 of their papers we have counts for
5 papers
Transferring Knowledge for Food Image Segmentation using Transformers and Convolutions
Grant Sinha, Krish Parmar, Hilda Azimi +4
Food image segmentation is an important task that has ubiquitous applications, such as estimating the nutritional value of a plate of food. Although machine learning models have be…
A Trustworthy Framework for Medical Image Analysis with Deep Learning
Kai Ma, Siyuan He, Pengcheng Xi +3
Computer vision and machine learning are playing an increasingly important role in computer-assisted diagnosis; however, the application of deep learning to medical imaging has cha…
COVID-Net UV: An End-to-End Spatio-Temporal Deep Neural Network Architecture for Automated Diagnosis of COVID-19 Infection from Ultrasound Videos
Hilda Azimi, Ashkan Ebadi, Jessy Song +2
Besides vaccination, as an effective way to mitigate the further spread of COVID-19, fast and accurate screening of individuals to test for the disease is yet necessary to ensure p…
Improving Classification Model Performance on Chest X-Rays through Lung Segmentation
Hilda Azimi, Jianxing Zhang, Pengcheng Xi +4
Chest radiography is an effective screening tool for diagnosing pulmonary diseases. In computer-aided diagnosis, extracting the relevant region of interest, i.e., isolating the lun…
COVID-Net US: A Tailored, Highly Efficient, Self-Attention Deep Convolutional Neural Network Design for Detection of COVID-19 Patient Cases from Point-of-care Ultrasound Imaging
Alexander MacLean, Saad Abbasi, Ashkan Ebadi +6
The Coronavirus Disease 2019 (COVID-19) pandemic has impacted many aspects of life globally, and a critical factor in mitigating its effects is screening individuals for infections…