This seminar will describe the speaker’s work in artistic image rendering and stylization, also called Non-Photorealistic Rendering.
Category: AIR Seminars
This seminar will present recent long-term recurrent network models that learn cross-modal description and explanation, using implicit and explicit approaches, which can be applied to domains including fine-grained recognition and visuomotor policies.
Regina Barzilay is a professor in the Department of Electrical Engineering and Computer Science and a member of the Computer Science and Artificial Intelligence Laboratory at the Massachusetts Institute of Technology. Her research interests are in natural language processing.
Led by Kate Saenko, Stan Sclaroff, Brian Kulis, and Margrit Betke, the initiative was featured during the Data Science Initiative’s BUDS 2018 conference and has launched an exciting seminar series for the spring 2018 semester that will feature top AI experts from across the country.
As artificial intelligence (AI) becomes more and more commonplace, the demand for these tools to reduce mistakes and become more transparent has created a critical need for advanced research. Bolstered by a $7.55 million grant from the Defense Advanced Research Projects Agency (DARPA), Kate Saenko, assistant professor of computer science and core faculty member of the AI Research (AIR) Initiative at BU, and UC-Berkeley faculty Trevor Darrell are working to uncover new ways to understand the decision-making processes of AI tools.
Brian Kulis joined BU in the fall of 2015, bringing his expertise in machine learning and artificial intelligence (AI) to key research and teaching thrusts of the university. An assistant professor of electrical and computer engineering and the inaugural Levine Career Development Professor, Kulis leverages AI and machine learning to advance the rapidly expanding field of data science.
Dr. Mike Jones, Senior Principal Research Scientist, Mitsubishi Electric Research Labs Wednesday, December 13, 1:00-2:00pm; MCS 148 (111 Cummington Mall, Boston) Abstract: The standard framework for using a convolutional neural network (CNN) for face verification is to compare the feature vectors taken from the penultimate network layer of a CNN trained to classify the identity of an input […]
Zhengming Ding, Graduate Student, Northeastern University Wednesday, December 6, 1:00-2:00pm; Hariri Institute for Computing (111 Cummington Mall, Boston) Abstract: It is essential to adapt previous well-organized knowledge to facilitate the challenging face recognition tasks, e.g., missing modality and one-shot issues. First of all, transfer learning may fail if no target evaluated face data are available in […]
Andrei Barbu, Research Scientist, Massachusetts Institute of Technology (MIT) Wednesday, November 15, 1:00-2:00pm; Hariri Institute for Computing (111 Cummington Mall, Boston) Abstract: We will discuss a program to unify research around a number of vision-language problems into a single mathematical framework culminating in a robotic platform that is able to follow natural language commands, store knowledge, and answer questions. […]
Guorong Li, Associate Professor, University of Chinese Academy of Sciences Wednesday, November 8, 1:00-2:00pm; Hariri Institute for Computing (111 Cummington Mall, Boston) Abstract: With the increasing prevalence of digital camera, images and videos have become the necessary part of people’s life. It is important to analyze videos, images and understand them automatically. In this talk, I will […]