EC60502: Pattern Recognition And Image Understanding
| EC60502 | |||||||||||||||||||||||||||||
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| Course name | Pattern Recognition And Image Understanding | ||||||||||||||||||||||||||||
| Offered by | Electronics & Electrical Communication Engineering | ||||||||||||||||||||||||||||
| Credits | 4 | ||||||||||||||||||||||||||||
| L-T-P | 3-1-0 | ||||||||||||||||||||||||||||
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| Semester | Spring | ||||||||||||||||||||||||||||
Syllabus[edit | edit source]
Syllabus mentioned in ERP[edit | edit source]
Pre-requisites: EC61501Pattern Representation: features, feature vectors; Supervised classification: Bayesâ Rule, Bayesâ classifier, minimum risk classifier, minimum distance classifier, PDF estimation from samples, lLnear discriminator, Perceptron criterion, MSE criterion, Multi class classification, KeslerâÂÂs construction, Ho-Kashyap procedure; Unsupervided classification: Nearest neighbor, KNN classifier, MSE clustering, k-means clustering, fuzzy kmeans clustering; Neural Pattern Recognition: Probabilistic neural network, multi-layer perceptron; Image understanding: Review of segmentation, Image component description â boundary representation, region representation; Image component representation: feature vector representation, graphical representation; Image Interpretation: Pattern recognition techniques, graphical techniques.