At the forefront of technological innovation, Emma Wadsworth, an electrical and computer engineering major, is transforming the way we integrate thermal and visual imaging. Her project aims to develop a machine learning model that can seamlessly translate between thermal (infrared) and RGB (visual) images, a critical advancement for applications ranging from autonomous navigation to environmental monitoring.
Wadsworth embarked on this journey from a simple class project, driven by curiosity and a passion for unexplored territories in imaging technology. “It started in a class,” she said. “I devoted far more hours than were probably reasonable, and I kind of fell in love.”
The crux of Wadsworth’s work addresses a significant challenge: the limitations of thermal imaging, such as lower resolution and the high cost of thermal cameras.
Navigating the complexities of research, Wadsworth acknowledges the lack of a predefined path. “There’s not a blueprint already for how to do most research problems,” she said. “It’s the most interesting and difficult part of it because that’s not something they teach you in school.” This statement not only reflects the challenges she faced but also her determination to contribute meaningful advancements to the field.
Emma Wadsworth’s project not only offers a promising leap forward in the capabilities of machine learning and image processing but also sets the stage for future innovations in how we perceive and utilize imaging technology across various spectrums.
More articles like this in ‘Student Innovation @ the U!’
Find this article and a lot more in the 2024 “Student Innovation @ the U” report. The publication is presented by the Lassonde Entrepreneur Institute to celebrate student innovators, change-makers, and entrepreneurs.
