Imaging Science Seminar: Foundations for Transforming the Imaging ChAIn
Imaging Science Seminar
Foundations for Transforming the Imaging ChAIn
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Dr. Derek J. Walvoord
L3Harris, Space and Airborne Systems Segment Adjunct Professor
College of Science, Rochester Institute of Technology
Rochester Institute of Technology
Abstract:
This seminar explores the profound impact of Machine Learning (ML) and Artificial Intelligence (AI) on the modern Imaging chAIn while emphasizing consistency in mathematical foundations. Correlations within the historical progression of the Imaging field may help indicate its future direction. However, this seminar attempts to achieve the same goal by instead exploring the historical progression of correlation itself. From projections, to transformers, to foundation models and agentic AI for Computer Vision (CV), consistencies are dissected to ground our understanding. Additionally, we present a two-pronged approach to improving CV generalization in open-world settings. First, we use an agentic AI workflow to simplify and expand the domain over which synthetic data can be produced. Second, we stress the value of injecting broad domain knowledge from pretrained vision-language models (VLMs) into solutions otherwise dominated by raster data processing. These concepts are reviewed in the context of our research and development in re-identification (reID) - a task now ubiquitous in multi-camera video collection settings, such as retail analytics, autonomous vehicles, and facility security. We demonstrate qualitative gains over component-level approaches and emphasize foundation model integration into custom CV applications.
Bio:
Dr. Derek J. Walvoord is a Fellow and Chief AI Architect for the Space & Airborne Systems Segment of L3Harris. With over 17 years at the company, Derek has experience in photogrammetric sensor modeling, rare event analysis, and Machine Learning for image and video exploitation problems. Derek holds a BS and PhD in Imaging Science from the Rochester Institute of Technology, where he has remained actively involved as an adjunct professor.
Intended Audience:
Beginners, undergraduates, graduates. Those with interest in the topic.
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