KAUST CEMSE AMCS STAT Graduate Seminar A Rapid, Accurate and Machine-agnostic Segmentation and Quantification Method for CT-based COVID-19 Diagnosis
A Rapid, Accurate and Machine-agnostic Segmentation and Quantification Method for CT-based COVID-19 Diagnosis
Xin Gao
Thursday, April 08, 12:00
- 13:00
https://kaust.zoom.us/j/94262797011?pwd=ZXBBcnltQ3JvZkdhWFZjTEptL3FmUT09
Graduate Seminar
KAUST-CEMSE-ECE-Ultraviolet semiconductor technologies for COVID-19 and beyond.png
Ultraviolet semiconductor technologies for COVID-19 and beyond
Xiaohang Li
Sunday, November 01, 12:00
- 13:00
https://kaust.zoom.us/j/92588396271
Graduate Seminar
Coronavirus testing made quick and easy
11 months ago
KAUST scientists develop virus mutation tracker
11 months 3 weeks ago
KAUST startup tackles COVID using AI and robotics
1 year 6 months ago
Peering under the "hood" of SARS-CoV-2
1 year 6 months ago
Professor Hussain’s adaptive tech for distance learning project receives $20,000 in prize funding
1 year 9 months ago
How AI helps improve COVID-19 testing
1 year 9 months ago
Studying COVID-19’s envelope protein
1 year 9 months ago
A shock to the system
1 year 10 months ago
Membrane makeover makes face mask reusable
1 year 10 months ago
Making the invisible, visible
1 year 10 months ago
AI that's built to save lives
1 year 11 months ago