Course Details
Subject {L-T-P / C} : BM6334 : Pattern Recognition { 3-0-0 / 3}
Subject Nature : Theory
Coordinator : Dr. Mirza Khalid Baig
Syllabus
Pattern Recoginiton- overview, Types of Pattern Recognition, Feature extraction-Statistical Pattern Recognition-Supervised & Unsupervised Learning Bayes decision Theory, Linear discriminant functions.
Parametric methods- ML & MAP estimation, Bayesian estimation, Non Parametric methods- Density estimation, Parzen Windows, Probabilistic Neural Networks (PNNs).
Unsupervised clustering- Tree clustering- K-means clustering,Linear models for classification and regression, Linear Discriminant Functions Perceptron-Learning Algorithm and convergence proof, Linear Least Squares Regression LMS algorithm.
Model free technique – ROC Curve, Classifier evaluation, Back propagation learning, Competitive learning
Course Objectives
- To gain an understanding of pattern recognition systems and statistical tools used in implementing pattern recognition systems.
- To understand the usage of different pattern recognition systems
- To gain skills for developing pattern recognition systems for healthcare applications.
Course Outcomes
After completing the course, the students will able to <br />1. Understand and apply mathematical concepts required for foundational understanding of pattern recognition. <br />2. Understand different modules/steps involved in the development of pattern recognition systems. <br />3. Use mathematical concepts for in-depth analysis and exploration of data in the context of pattern recognition. <br />4. Learn to use state-of-the-art tools and methods for development of pattern recognition systems. <br />5. Conceptualise and design pattern recognition systems for complex tasks related to healthcare applications while keeping in mind ethical requirements related to healthcare applications.
Essential Reading
- Duda R O, Hart P E, and Stork D G, Pattern classification, John Wiley and Sons
- Christopher M B, Pattern Recognition and Machine Learning, Springer
Supplementary Reading
- Robert Schalkoff, Pattern recognition, Statistical, Structural and neural approaches, John Wiley and Sons
- Fu K S, Syntactic Pattern recognition and applications, Prentice Hall