01 Ιουλ 2019

Invited Lecture of Prof. Konstantinos Plataniotis

Professor Konstantinos N. Plataniotis (IEEE Fellow, Bell Canada Chair in Multimedia, Department of Electrical & Computer Engineering, University of Toronto, Canada) is going to lecture on

 Machine Learning in Engineering: Panacea or Deep Trouble?

 at Auditorium III of Aristotle University Research Dissemination Center – ΚΕΔΕΑ ΑΠΘ (September 3rd Ave., University Campus) on Thursday July 18th, 2019, at 10:45. The lecture is given in the context of the 1st EURASIP-GAIPDM Seasonal School on “Learning from Signals, Images, and Video” (https://gaipdm-schools.web.auth.gr/)  and is open to the academic community of Aristotle University.

 

 ABSTRACT

The recent rise of artificial intelligence can be attributed to the success of deep neural networks in tasks, such as image classification and natural language processing. The availability of curated, large scale, and diverse data sets, as well as the access to powerful computing infrastructure, and theoretical advances are the main driving factors behind the resurgence. Machine learning, deep neural networks, smart analytics are all trending tools promising disruptive contributions capable of solving real-world problems. Thus, it is not surprising to see a sustained push from industry, policy makers, and government bodies towards accelerating developments in machine learning. The purpose of this presentation is to provide an environmental scan of the research landscape, introduce, in a tutorial style, aspects of the research machinery, and discuss intuition, utility, and expectations.

 Presentation slides

About the Speaker:

 

Konstantinos N. Plataniotis     

Professor

Bell Chair in Multimedia

Department of Electrical and Computer Engineering

University of Toronto

Sandford Fleming Bldg., Room 540

10 King's College Road, Toronto, ON, M5S3G4, CANADA
email: kostas AT ece DOT utoronto DOT ca
www:  https://www.comm.utoronto.ca/~kostas/

 

 

Konstantinos N. Plataniotis, Bell Canada Chair in Multimedia, is a Professor with the ECE Department at the University of Toronto. His current research interests are: machine learning, adaptive systems & pattern recognition, image & signal processing, communications systems, and big data analytics. He is a registered professional engineer in Ontario, Fellow of the IEEE and Fellow of the Engineering Institute of Canada. Dr. Plataniotis was the IEEE Signal Processing Society Inaugural Vice President for Membership (2014-2016) and the General Co-Chair for the IEEE GlobalSIP 2017 (November 2017, Montreal, Q.C.). He co-chairs the 2018 IEEE International Conference on Image Processing (ICIP 2018), October 7-10, 2018, Athens Greece, and the 2021 IEEE International Conference in Acoustics, Speech and Signal Processing (ICASSP 2021), Toronto, ON, Canada