Using Analogy to Recognize Visual Situations
Speaker: Dr. Melanie Mitchell, Portland State University and Santa Fe Institute
Join us for refreshments starting at 2pm. The lecture will start at 2:30pm and run till approximately 3:30pm. A Q&A with the speaker will follow the lecture.
Enabling computers to recognize abstract visual situations remains a hard open problems in artificial intelligence. No machine vision system comes close to matching human ability at identifying the contents of images or visual scenes, or at recognizing abstract similarity between different scenes, even though such abilities pervade human cognition. In this talk I will describe my research on getting computers to flexibly recognize visual situations by integrating neural networks for low-level vision with an agent-based model of higher-level concepts and analogy-making.
Melanie Mitchell is Professor of Computer Science at Portland State University, and External Professor and Member of the Science Board at the Santa Fe Institute. She received a Ph.D. in Computer Science from the University of Michigan. Her dissertation, in collaboration with her advisor Douglas Hofstadter, was the development of Copycat, a computer program that makes analogies. She is the author or editor of five books and over 70 scholarly papers in the fields of artificial intelligence, cognitive science, and complex systems. Her most recent book, Complexity: A Guided Tour (Oxford, 2009), won the 2010 Phi Beta Kappa Science Book Award. It was also named by Amazon.com as one of the ten best science books of 2009, and was longlisted for the Royal Society’s 2010 book prize. Melanie directs the Santa Fe Institute’s Complexity Explorer project, which offers online courses and other educational resources related to the field of complex systems.
To register for the event, please use the form below or visit Eventbrite.
If you’re unable to join us at the lecture, a video of the talk will be available on this page 2-3 weeks after the event.