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Pattern Recognition and Application

By Prof. Prabir Kumar Biswas   |   IIT Kharagpur
Learners enrolled: 852
The course has been designed to be offered as an elective to final year under graduate students mainly from Electrical Sciences background. The course syllabus assumes basic knowledge of Signal Processing, Probability Theory and Graph Theory. The course will also be of interest to researchers working in the areas of Machine Vision, Speech Recognition, Speaker Identification, Process Identification etc.
The course covers feature extraction techniques and representation of patterns in feature space. Measure of similarity between two patterns. Statistical, nonparametric and neural network techniques for pattern recognition have been discussed in this course. Techniques for recognition of time varying patterns have also been covered. Numerous examples from machine vision, speech recognition and movement recognition have been discussed as applications. Unsupervised classification or clustering techniques have also been addressed in this course.
Analytical aspects have been adequately stressed so that on completion of the course the students can apply the concepts learnt in real life problems.

INTENDED AUDIENCE: Any Interested Learners
PRE-REQUISITES        : Nil
Summary
Course Status : Ongoing
Course Type : Elective
Duration : 12 weeks
Start Date : 26 Jul 2021
End Date : 15 Oct 2021
Exam Date : 23 Oct 2021 IST
Enrollment Ends : 09 Aug 2021
Category :
  • Electrical, Electronics and Communications Engineering
Credit Points : 3
Level : Undergraduate/Postgraduate



Course layout

Week 1 : Introduction
              
Feature Extraction - I
              
Feature Extraction - II

Week 2
Bayes Decision Theory - I
               Bayes Decision Theory - II

Week 3 :  
Normal Density and Discriminant Function - I
                Normal Density and Discriminant Function - II
                
Bayes Decision Theory - Binary Features

Week 4 : 
Maximum Likelihood Estimation
               Probability Density Estimation - I

Week 5 : 
Probability Density Estimation - II
                Probability Density Estimation - III
                Probability Density Estimation  - IV

Week 6 : Dimensionality Problem
                Multiple Discriminant Analysis

Week 7 : Principal Component Analysis - Tutorial
                Multiple Discriminant Analysis - Tutorial
                Perceptron Criteria  - I

Week 8 : Perceptron Criteria  - II
               MSE Criteria
 
Week 9 : Linear Discriminator Tutorial
                Neural Network - I
                Neural Network - II
 
Week 10 : Neural Network -III/ Hopefield Network
                  RBF Neural Network - I
                  
 Week 11 : RBF Neural Network - II
                  Support Vector Machine
                  Clustering -I
 
Week 12 : Clustering -II
                 Clustering -III


                
                

           


Books and references

Nil

Instructor bio



Prof. Prabir Kumar Biswas
received his B.Tech., M.Tech., and Ph.D. degrees in Electronics and Electrical Communication Engineering from the Indian Institute of Technology Kharagpur in 1985,1989, and 1991 respectively. He served Bharat Electronics Ltd. (BEL), Ghaziabad as a DeputyEngineer during the period 1985 to 1987. In 1991 he joined the faculty of the Department of Electronics and Electrical Communication Engineering at IIT Kharagpur where he is presently a Professor and also holding the position of Head of the Department. He served as the Head of the Computer and Informatics Center at IIT Kharagpur from March 2008 to December 2014. Prof. Biswas visited the University of Kaiserslautern, Germany during March 2002 to February 2003 as Alexander von Humboldt Fellow. His research interests are in image and video processing, pattern recognition, multimedia systems etc. He has supervised 12 doctoral students, and published more than 100 research papers in various international and national journals and conference proceedings in these areas. He has prepared four online Video Courses under NPTEL program. Prof. Biswas is a Senior Member of the IEEE. He also holds life membership of Indian Unit of Pattern Recognition and Artificial Intelligence (IUPRAI, India). He has served as a member of technical program committees of several national and international conferences, and served as Organizing Chair of Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP) in 2008.

Course certificate

The course is free to enroll and learn from. But if you want a certificate, you have to register and write the proctored exam conducted by us in person at any of the designated exam centres.
The exam is optional for a fee of Rs 1000/- (Rupees one thousand only).
Date and Time of Exams: 23 October 2021 Morning session 9am to 12 noon; Afternoon Session 2pm to 5pm.
Registration url: Announcements will be made when the registration form is open for registrations.
The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published. If there are any changes, it will be mentioned then.
Please check the form for more details on the cities where the exams will be held, the conditions you agree to when you fill the form etc.

CRITERIA TO GET A CERTIFICATE

Average assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.
Exam score = 75% of the proctored certification exam score out of 100

Final score = Average assignment score + Exam score

YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75. If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.

Certificate will have your name, photograph and the score in the final exam with the breakup.It will have the logos of NPTEL and IIT Kharagpur .It will be e-verifiable at nptel.ac.in/noc.

Only the e-certificate will be made available. Hard copies will not be dispatched.

Once again, thanks for your interest in our online courses and certification. Happy learning.

- NPTEL team


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