David Stork

Dr. David G. Stork is widely considered a pioneer in the application of rigorous computer vision, image analysis and artificial intelligence to problems in the history and interpretation of fine art. He is a graduate of MIT and the University of Maryland, and has published 200+ scholarly papers and eight books, including Pattern classification (2nd ed.) by Duda, Hart, and Stork, and the forthcoming Pixels & paintings: Foundations of computer-assisted connoisseurship (Wiley). He has held faculty appointments in eight disciplines, and is currently a visiting lecturer at Stanford University.

projects by David Stork

Deep Neural Networks for Image Segmentation in Fine Art

5 weeks · 5-7 hours per week · INTERMEDIATE

Included with a Manning Online subscription

catalog / Data Science

In this liveProject, you’ve taken on the challenge of digitizing the collection of the World Painting Museum, and the head curator wants you to use your machine learning skills to create an index of the art. Your challenges will include classifying your training data, considering pretrained models to help aid categorization, implementing a customized CNN that can identify genre, and applying image semantic segmentation in order to facilitate the classification by identifying the elements present on the art painting.