Events

Abstract

The Atomic Force Microscope (AFM) is an instrument for measuring, in fact “seeing”, phenomena at nanoscale (10−9m) and all the way down to the atomic scale (<10−10m). It was borne out of a need to observe physical reality below the resolution of optical microscopes. Invented in 1986 by Binnig, it has aided scientists, researchers, and engineers spanning many scientific and industrial domains. The typical sensing apparatus of the AFM is a very sharp tip (a few atoms wide) attached to the free-end of a fixed-free micro-beam.

University of Waterloo Tape Music Club (UWTMC) is back in a big way this term, with a semi-weekly jam session during your lunch break on Mondays and Wednesdays! Come make music and make community with folks. No skills or instruments are required. Everyone is invited and welcome - all skill levels, genres, and experiences!

The sessions start January 11^th in the E7 1^st Floor Ideas Clinic on UW Main Campus and run from 12-1:30 p.m.

The Emergent Encounters Action Project, in collaboration with AACFTDOAPORUCACIAWOMW, is running a 3-part block printing workshop! All materials and tools are provided. 

Session 1 - Jan 17th - 12:00 - 1:00 p.m. in E5-6008:

Come see a printing process from design to layout to carving to printing. This session will introduce one approach to take an idea in your head and turn it into a finished print. There will also be time to let you roll and pull some prints!

Session 2 - Jan 24th - 12:00 - 1:00 p.m. in E5-6008:

Abstract

Sea ice mapping on synthetic aperture radar (SAR) imagery is important for various purposes, including ship navigation and usage in environmental and climatological studies. Although a series of deep learning-based models have been proposed for automatic sea ice classification on SAR scenes, most of them are flat N-way classifiers that do not consider the uneven visual separability of different sea ice types. To further improve classification accuracy with limited training samples, a hierarchical deep learning-based pipeline is proposed for sea ice mapping from SAR.

The Emergent Encounters Action Project, in collaboration with AACFTDOAPORUCACIAWOMW, is running a 3-part block printing workshop! All materials and tools are provided. 

Session 1 - Jan 17th - 12:00 - 1:00 p.m. in E5-6008:

Come see a printing process from design to layout to carving to printing. This session will introduce one approach to take an idea in your head and turn it into a finished print. There will also be time to let you roll and pull some prints!

Session 2 - Jan 24th - 12:00 - 1:00 p.m. in E5-6008:

The Emergent Encounters Action Project, in collaboration with AACFTDOAPORUCACIAWOMW, is running a 3-part block printing workshop! All materials and tools are provided. 

Session 1 - Jan 17th - 12:00 - 1:00 p.m. in E5-6008:

Come see a printing process from design to layout to carving to printing. This session will introduce one approach to take an idea in your head and turn it into a finished print. There will also be time to let you roll and pull some prints!

Session 2 - Jan 24th - 12:00 - 1:00 p.m. in E5-6008:

Systems Design Engineering and Biomedical Engineering students, faculty, and staff are invited to show off their community spirit by dressing for each Spirit Week daily theme!

Join the Centre for Society, Technology and Values for a FREE movie screening (+ free popcorn!) of Star Wars Kid in E5-6004.

Abstract

Inflammatory Bowel Disease (IBD) refers to a group of conditions that primarily affect the gut and cause inflammation. In contrast, Hidradenitis Suppurativa (HS) is a chronic immune-mediated condition characterized by boils in a person's underarms, groyne, and/or under their breasts. In recent years, the research on HS has been gaining a growing level of interest in light of reliable recognition of these two diseases (i.e., IBD and HS) becoming crucial in clinical settings.

Abstract

Achieving reliable and robust performance of visual perception systems with Artificial Intelligence (AI) in real-world industrial applications can be challenging due to highly dynamic conditions and requirements. Traditional AI-based solutions require offline training on high-quality data, making it difficult to accommodate new technologies, data, hardware, tasks, and customer needs without retraining.