Statistical modeling of data, Naïve Bayes’ methods, techniques of parametric and non-parametric estimation, supervised classifiers such as hidden markov models, linear discriminant functions and non-linear discriminant functions including neural networks and support vector machines, unsupervised classifiers (various clustering techniques), hybrid classifiers (or semi-supervised learning) and stochastic learning.
Enhancement of images in the space and frequency domain, histogram processing of images, various segmentation techniques, object localization in video frames/ images, classification of video frames, content-based video indexing.
Tokenization, parts-of-speech tagging, creating dictionaries and searching through them, automated summary generation, processing of natural language text and organizing the output for information retrieval.
Rule-based classifiers, association mining, generation of and searching through frequent pattern trees, generation of association rules, sequential pattern mining of data.
