Get our free extension to see links to code for papers anywhere online!

Chrome logo  Add to Chrome

Firefox logo Add to Firefox

COVID-Net USPro: An Open-Source Explainable Few-Shot Deep Prototypical Network to Monitor and Detect COVID-19 Infection from Point-of-Care Ultrasound Images


Jan 04, 2023
Jessy Song, Ashkan Ebadi, Adrian Florea, Pengcheng Xi, Stéphane Tremblay, Alexander Wong

Add code

* 12 pages, 5 figures 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

A Trustworthy Framework for Medical Image Analysis with Deep Learning


Dec 06, 2022
Kai Ma, Siyuan He, Pengcheng Xi, Ashkan Ebadi, Stéphane Tremblay, Alexander Wong

Add code


   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

On the evolution of research in hypersonics: application of natural language processing and machine learning


Aug 17, 2022
Ashkan Ebadi, Alain Auger, Yvan Gauthier

Add code

* 18 pages, 9 figures 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Towards Trustworthy Healthcare AI: Attention-Based Feature Learning for COVID-19 Screening With Chest Radiography


Jul 19, 2022
Kai Ma, Pengcheng Xi, Karim Habashy, Ashkan Ebadi, Stéphane Tremblay, Alexander Wong

Add code

* Accepted to 39th International Conference on Machine Learning, Workshop on Healthcare AI and COVID-19 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Women, artificial intelligence, and key positions in collaboration networks: Towards a more equal scientific ecosystem


May 19, 2022
Anahita Hajibabaei, Andrea Schiffauerova, Ashkan Ebadi

Add code

* 20 pages, 6 figures 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

COVID-Net UV: An End-to-End Spatio-Temporal Deep Neural Network Architecture for Automated Diagnosis of COVID-19 Infection from Ultrasound Videos


May 18, 2022
Hilda Azimi, Ashkan Ebadi, Jessy Song, Pengcheng Xi, Alexander Wong

Add code


   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Detecting Emerging Technologies and their Evolution using Deep Learning and Weak Signal Analysis


May 11, 2022
Ashkan Ebadi, Alain Auger, Yvan Gauthier

Add code

* 17 pages, 8 figures, 2 tables (preprint version) 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Improving Classification Model Performance on Chest X-Rays through Lung Segmentation


Feb 22, 2022
Hilda Azimi, Jianxing Zhang, Pengcheng Xi, Hala Asad, Ashkan Ebadi, Stephane Tremblay, Alexander Wong

Add code


   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Performance or Trust? Why Not Both. Deep AUC Maximization with Self-Supervised Learning for COVID-19 Chest X-ray Classifications


Dec 14, 2021
Siyuan He, Pengcheng Xi, Ashkan Ebadi, Stephane Tremblay, Alexander Wong

Add code

* Published at CVIS 2021: 7th Annual Conference on Vision and Intelligent Systems 
* 3 pages 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

NRC-GAMMA: Introducing a Novel Large Gas Meter Image Dataset


Nov 12, 2021
Ashkan Ebadi, Patrick Paul, Sofia Auer, Stéphane Tremblay

Add code

* 12 pages, 7 figures, 1 table 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email
1
2
>>