Vishwakarma Institute of Technology Issue 05 : Rev No. 0 : Dt. 13/03/15 Course Plan Format Academic Year : 2015-16 FF No. 182 Branch : Electronics, E&TC Semester : I Subject Name : Pattern Recognition Subject Code: EC 42103, EC 42203 Unit No. I Topic Method Media Machine perception, Pattern Lecture recognition systems, design cycle, learning and adaptation. Board – Chalk II Bayesian Decision theory Lecture continuous and discrete features, minimum error rate classification, classification discriminant function, Parameter estimation methods like Maximum-Likelihood estimation, Gaussian mixture models, Expectationmaximization method, and Bayesian estimation. Board – Chalk III Parzen-window method, K-Nearest Lecture Neighbour method, metrics and NearestNeighbor Classification. Board – Chalk Student Activity Assessment Tool Tut: Questions based i)TestI: Explanation on Concept of type questions – 100 pattern recognition % weitage and Machine ii)Timely submission of completed home perception. assignment iii)Tutorial assessment is based on MCQ based questions: one before Test II and other before ESE Tut: Analysis of i) MCQ based Test II Bayesian Decision ii)Timely submission theory continuous of completed home and discrete features, assignment Analysis of iii)Tutorial assessment is based on MCQ Maximumbased questions: one Likelihood before Test II and estimation other before ESE Matlab based execution of the tutorial Tut: Analysis of i) MCQ based Test II Minimum Distance ii)Timely submission Classifier, Parzen of completed home assignment Remarks Test I out of 30 marks, to be converted to 10 marks Test II out of 20 marks, to be converted to 20 marks Vishwakarma Institute of Technology Issue 05 : Rev No. 0 : Dt. 13/03/15 Windows and iii)Tutorial assessment is based on MCQ Neighbour method Matlab execution tutorial IV Linear discriminant function and Lecture decision surface, Perceptron, Support vector machines Board – Chalk V Criterion functions for clustering, Lecture Algorithms for clustering: Kmeans, Hierarchical and other methods, Cluster validation, component analysis. Board – Chalk based based questions: one of the before Test II and other before ESE Tut: Analysis of i)Timely submission Linear discriminant of completed home function, Analysis of assignment Support vector ii)Tutorial assessment is based on MCQ machines based questions: one before Test II and other before ESE Tut: Analysis of i)Timely submission Algorithms for of completed home assignment clustering ii)Tutorial assessment is based on MCQ based questions: one before Test II and other before ESE Levels of Bloom’s Taxonomy applicable for the course – Knowledge / Comprehension / Application / Analysis / Synthesis / Evaluation (Strike out levels not applicable) List of Reference Books and Text Books - 1. Pattern Classification, R.O.Duda, P.E.Hart and D.G.Stork, John Wiley, 2001 2. Pattern Recognition, S.Theodoridis and K.Koutroumbas, 4th Ed., Academic Press, 2009 3. Pattern Recognition and Machine Learning, C.M.Bishop, Springer, 2006 #§◘■□- Details of laboratory course student activity for experiments based on appropriate unit. Details of Tutorial course student activity based on appropriate unit. Mandatory Assessment activities as per structure. Mode of conduct of class test is to be mentioned. Scope of HA should be written in brief. Write unit-wise parameters used for continuous assessment of laboratory course. Vishwakarma Institute of Technology ○- Issue 05 : Rev No. 0 : Dt. 13/03/15 If parameters are used as a whole, they may be described in footer. Write unit-wise parameters used for continuous assessment of tut. course. Name and Signature of Faculty executing the course plan 1) P. A. Kulkarni 2) _____________________________________________ 3) _____________________________________________ ……. ……. Signature of Chairman – BOS Date : 28 / 3 / 2015