IEEE CIS and C Chapters Lecture on Advancements and Applications of Generative Adversarial Networks
IEEE CIS and C Chapters are excited to host technical talk on Advancements and Applications of Generative Adversarial Networks.
Speaker 1: Dr. Raghuveer Rao
Speaker 2: Prasanna R. Pulakurthi
Speaker 3: Dr. Sohail A. Dianat
Cost:
- $10 for IEEE Members (Includes 1 PDH credit)
- $15 for Non-IEEE Members (Includes 1 PDH credit)
- Free for General Admission (No PDH credit)
- Free for Student and Graduate Student Members (No PDH credit)
(All payments must be received by June 05, 2024).
Time: Thursday, June 06, 2024 at 12 PM, EDT
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This IEEE talk will be held in-person and via WebEx for virtual attendees.
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Meeting number: 2539 067 2892
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Abstract:
Generative Adversarial Networks (GANs) are a branch of generative models that offer exceptional capability in generating realistic images, audio, video, and various data forms. The first talk will provide a perspective on the utility of scene synthesis for training machine learning models. The second talk will focus on the recent advancements in GANs. Neural Architecture Search (NAS) aims to automate the search for an optimal architecture that meets specific performance criteria, significantly reducing the manual effort involved in model design. The recent surge in network compression underscores the necessity to make these powerful models more accessible and efficient, particularly for resource-constrained environments. This talk presents a new training procedure that leverages NAS to discover the optimal architecture for image generation while employing the Maximum Mean Discrepancy (MMD) repulsive loss for adversarial training. Moreover, the generator network is compressed using tensor decomposition to reduce its computational footprint and inference time while preserving its generative performance and allowing it to be deployed on edge devices.
Date and Time
Location
Hosts
Registration
- Date: 06 Jun 2024
- Time: 04:00 PM UTC to 05:30 PM UTC
-
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- UAlbany ETEC Building
- Albany, New York
- United States 12203
- Building: ETEC Ops Command Center
- Room Number: 340
- Click here for Map
- Contact Event Hosts
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Lalit K. Mestha (lkmestha@gmail.com)
Alkesh V. Patel (alkesh.v.patel@ieee.org)
- Starts 25 May 2024 04:00 AM UTC
- Ends 07 June 2024 03:00 AM UTC
- Admission fee ?
Speakers
Raghuveer of DEVCOM Army Research Laboratory
Biography:
Dr. Raghuveer Rao is the Chief of the Intelligent Perception Branch at the DEVCOM Army Research Laboratory (ARL) in Adelphi, Maryland, where he oversees R&D in multimodal computer vision and applications, mainly to autonomous systems and scene understanding. Prior to joining ARL, Dr. Rao was a professor of electrical engineering and imaging science at the Rochester Institute of Technology. He has also held visiting appointments with the Indian Institute of Science, the US Air Force Research Laboratory, the US Naval Surface Warfare Center, and Princeton University. He has made multiple research contributions to signal & image processing, communication, and computer vision, and serves as an ABET program evaluator for electrical engineering. Dr. Rao is a life fellow of IEEE and an elected fellow of SPIE.
Email:
Address:Army Research Laboratory (ARL), , Adelphi , Maryland, United States, 20783
Prasanna of Rochester Institute of Technology
Biography:
Prasanna Reddy Pulakurthi is a Ph.D. candidate in the Electrical and Computer Engineering department at Rochester Institute of Technology (RIT). His primary research areas include Generative AI, Computer Vision, Machine Learning, and Deep Learning. He is particularly interested in the development and refinement of image generation, human action recognition, and image translation models.
Email:
Address:Rochester Institute of Technology (RIT), , Rochester, New York, United States, 14623
Sohail of Rochester Institute of Technology
Biography:
Dr. Sohail A. Dianat received a B.S. degree in Electrical Engineering from the Arya-Mehr University of Technology in Tehran, Iran, and his M.S. and D.Sc. degrees in Electrical Engineering from George Washington University. In September 1981, he joined the Rochester Institute of Technology, where he is currently a professor of Electrical Engineering and Imaging Science. Dr. Dianat has taught an assortment of undergraduate and graduate courses in the areas of digital signal/image processing and digital communication. His current research interests include digital signal/image processing and wireless communication.
Email:
Address:Rochester Institute of Technology (RIT), , Rochester, New York, United States, 14623