Connecting Vision and Language

#Deep #learning #vision #language
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Rochester CS/CIS chapter technical presentation



  Date and Time

  Location

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  Registration



  • Date: 08 Sep 2017
  • Time: 11:00 AM to 12:30 PM
  • All times are (GMT-05:00) US/Eastern
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  • 150 Lomb Memorial Dr.
  • Rochester , New York
  • United States 14623
  • Building: Golisano Hall (GOL)
  • Room Number: 1610
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  • Starts 23 August 2017 12:00 AM
  • Ends 07 September 2017 11:00 PM
  • All times are (GMT-05:00) US/Eastern
  • No Admission Charge


  Speakers

Raymond Ptucha Raymond Ptucha

Topic:

Connecting Vision and Language

Deep learning has enabled incredible advances in computer vision, natural language processing, and general pattern understanding. Success in this space spans many domains including object detection, speech recognition, natural language processing, and action/scene interpretation. For targeted tasks, results are on par with and often surpass the abilities of humans.  Recent discoveries have enabled researchers to bridge the gap between visual and written stimulus.  For example, the automatic captioning of still imagery, summarization of video, and generation of images from keywords were all difficult tasks two years ago, but with the help of deep learning, are all active research today.  Despite great progress, the generic connection of various written and visual modalities remains challenging.  This talk will review recent advances in the vision and language domains and introduce a novel vector connection space such that words, sentences, and paragraphs can efficiently and accurately connect with still and motion visual stimuli. Similar deep learning techniques are being applied to everyday devices such as smartphones and wearables and will make our lives more efficient and feature rich. 

Biography:

Raymond Ptucha is an Assistant Professor in Computer Engineering and Director of the Machine Intelligence Laboratory at Rochester Institute of Technology. His research specializes in machine learning, computer vision, and robotics. Ray was a research scientist with Eastman Kodak Company where he worked on computational imaging algorithms and was awarded 31 U.S. patents with another 19 applications on file. He graduated from SUNY/Buffalo with a B.S. in Computer Science and a B.S. in Electrical Engineering. He earned an M.S. in Image Science from RIT. He earned a Ph.D. in Computer Science from RIT in 2013. Ray was awarded an NSF Graduate Research Fellowship in 2010 and his Ph.D. research earned the 2014 Best RIT Doctoral Dissertation Award. Ray is a passionate supporter of STEM education and is an active member of his local IEEE chapter and FIRST robotics organizations. 

Raymond Ptucha

Topic:

Connecting Vision and Language

Biography:






Agenda

11:00 am social with pizza

11:30 am presentation