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Hands-On Image and Video Analysis using Deep Learning Methods

News / Lectures/Workshops / Past / Hands-On Image and Video Analysis using Deep Learning Methods
23 July. 2019 | 09:00 | Julia House, 21612, CY1591, Themistokli Dervi 3, Nicosia 1066
Hands-On Image and Video Analysis
using Deep Learning Methods, 2-days Workshop


Prof. Marios S. Pattichis
Department of Electrical and Computer Engineering
The University of New Mexico
Albuquerque, NM, USA
 
23 - 24 July, 2019 

Please register your participation at research@rise.org.cy by the 18th July, 2019 

Organised by: RISE & IEEE Signal Processing Society and Engineering in Medicine and Biology Cyprus Chapters

 Abstract: Several image and video analysis problems have been greatly impacted by the development of recent Deep Learning methods. Applications range from image classification, object detection, image segmentation, to video activity classification.
The primary goal of the workshop will be to cover the essential elements that are needed to understand the essential characteristics of the deep learning architectures used in different applications in image and video analysis.

The 2-day workshop will cover the basic algorithms with example code on the first day, followed by hands-on implementations on the second day. Participants will be asked to install Anaconda, Tensorflow, and OpenCV on their laptops on the first day so that they can complete the assignments on the second day. The workshop will describe practical methods in Python for implementing, training, and testing custom architectures for particular applications. Example topics include 2D and  3D Convolutional neural nets (CNN), Residual Networks, Autoencoders, Random Forests, and Transfer learning.
  
Biography: Marios Pattichis received the B.Sc.(High Hons. and Special Hons.) in Computer Sciences and the B.A. (High Hons.) degree in Mathematics, both in 1991, the M.S. degree in Electrical Engineering in 1993, and the Ph.D. degree in computer engineering in 1998, all from the University of Texas, Austin. He is currently a Professor and Associate Chair with the Department of Electrical and Computer Engineering, University of New Mexico (UNM), Albuquerque. His current research interests include digital image, video processing, communications, dynamically reconfigurable computer architectures, and biomedical and space image-processing applications.

Dr. Pattichis is currently a Senior Associate Editor for the IEEE Transactions on Image Processing. He has previously served a Senior Associate Editor for the IEEE Signal Processing Letters, Associate Editor for the IEEE Transactions on Image Processing, IEEE Transactions on Industrial Informatics, and as a Guest Associate Editor for the IEEE Transactions on Information Technology in Biomedicine. At UNM, he is currently the director of the image and video Processing and Communications Lab (ivPCL). His research on large-scale video analysis methods is currently funded by the National Science Foundation. His efforts to teach Python and Raspberry Pis to teach the basics of programming to under-represented middle school students are also funded by the National Science Foundation.


 
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