This page is dedicated to deep learning algorithms that design new types of hardware. The primary focus of the work presented here is to showcase new and improved imaging systems (cameras, microscopes, CT, MRI), which are specifically optimized to collect data by and for deep learning tasks. Please find an introduction to this area of research here, and several example projects demonstrating this new effort below.
This website includes research from the Computational Optics Lab at Duke University. We develop new microscopes, cameras and computer algorithms to capture better biomedical images. The lab is directed by Dr. Roarke Horstmeyer , who is a new Assistant Professor in the Biomedical Engineering Department at Duke.
The Duke University engineering course, Machine Learning and Imaging, is now fully online. This class is an overview of machine learning and imaging science, with a focus on the intersection of the two fields. It offers much of the introductory material needed to understand the basics of machine learning for hardware design. Please find lectures, homeworks, example code and course projects here:
