On Mathematical Modeling in Image Reconstruction and Beyond

Explore a 44-minute lecture by Bin Dong on mathematical modeling in image reconstruction and its broader applications. Delve into the fundamental role of imaging in natural sciences, engineering, and daily life. Examine the significant advancements in mathematical models and algorithms for image reconstruction over the past three decades. Review the progress of two primary mathematical approaches: wavelet frame-based and PDE-based methods. Investigate the connections between these approaches and their implications. Discover how the study of these links has led to a mathematical understanding of deep convolutional neural networks, resulting in intriguing developments in deep learning, computational imaging, and scientific computing. Access accompanying presentation slides for a comprehensive visual aid to the lecture content.