Pattern Recognition and Image Analysis

(25th May-29th May, 2018)

in association with

Venue: Lal-Ded Auditorium Department of Computer Sc & IT,Bhaderwah Campus,University of Jammu

Last Date for Registration: May 21st, 2018

Eligibility: Faculty/PhD/Research Scholars of engineering/technical institutions and persons from Govt. departments/labs and industry.

Experts from Academia/Industry: Dr. Partha Pratim Roy (IITR), Dr. Baij Nath Kaushik (SMDV University)

Why Pattern Recognition and Image Analysis?

Pattern recognition and image analysis have become inevitable for the growth and development of new and emerging scenarios of Computer Engineering Sciences. It is so pervasive today that you probably use it dozens of times a day without knowing it. Its techniques are becoming indispensable and it holds great potential in the field of computer vision, image processing, medical imaging, natural language processing, speech processing etc. This course will help you to learn about the most effective techniques and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of learning but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems. You would also acquire the skills needed to work with the problems of kernel- based learning, ensemble learning, supervised learning algorithms and fuzzy logic concepts.

Objective of the Course

  • Introduction of Pattern Recognition.
  • Understanding of various state-of-art techniques in image/signal analysis.
  • Knowledge and hands-on training of various software for pattern recognition and image analysis.
  • Introduce real-life applications of the pattern recognition and image analysis.
  • Benefits and Outcomes of the Course

  • Learning of basic knowledge in the area of pattern recognition and image analysis.
  • Hands-on experience in working with different software in image analysis.
  • Understanding of using pattern recognition techniques for digital, medical and satellite imaging.

  • Course Program

  • The program is split into lectures and lab sessions.
  • Quizzes and project work for enhanced learning.
  • Hands-on experience on basic & advanced- level topics.
  • Interaction & learning with experts from academia & industry.
  • Certificates to the participants by E&ICT Academy IITR.

  • Course Content:
  • Introduction to Pattern Recognition.
  • Image Analysis and Pattern Recognition.
  • Kernel-based learning, ensemble learning.
  • Adaptive Linear NN, Multiple Adaptive NN, Back Propagation NN.
  • Introduction to Genetic Algorithms.
  • Dimension Reduction Algorithms.
  • Linear Classifiers and Deep Learning.
  • Fuzzy Logic Concepts, Fuzzy Membership, with Fuzzy operations.
  • Hands-on session on Supervised Learning Algorithms, Image Processing and PR.
  • Hands-on session on Neural Networks and Fuzzy using C/Python.
  • Important Details

    Last Date for Registration:
    May 21st, 2018
    40 seats on first-cum-first-serve basis
    5 days, 40 hours
    Registration Fee
    Faculty Members/Research scholars: Rs. 2,500/-
    Persons from Industry: Rs. 3,000/-
    Payment Details
    Demand draft drawn in favour of "Dean SRIC IIT Roorkee" payable at Roorkee
    How to Apply
    You can apply online by click here to fill-up the application form OR you can download offline form and email scanned copy to
    Contact Details
    Dr. Sanjeev Manhas (P.I., E&ICT Academy, ECE Dept, IITR)
    Dr. Partha Pratim Roy (Local co-ordinator, Assistant Prof. CSE Dept, IITR)
    Prof. GM Bhat (Hon'ble Rector Bhaderwah Campus, University of Jammu-Patron)
    Dr. Jatinder Manhas (CS & IT Dept. University of Jammu- Convener)
    Dr. Abid Sarwar (CS & IT Dept. University of Jammu-Organizing Secretary),
    Tel: +91-9697436894,+91-8082770939, +91-7078627392, +91-1332-286457

    A hard copy of the application form along with Demand Draft must reach to the following address: Mr. Prateek Sharma, EICT Academy, ECE Department, IIT Roorkee, Uttarakhand 247667.

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