Department of Computer Science and Engineering (CSE)

Image sampling and quantization; Image smoothing , sharpening and contrast enhancement in spatial and frequency domains: basic gray level transformation, histogram processing, image subtraction, image averaging, Gaussian and Laplacian filters in spatial and frequency domains, convolution theorem; Image de-noising: noise models, noise reduction by spatial and frequency domain filters, mean filter, adaptive filter, bandpass and band reject filters, notch filter, inverse filter, minimum mean square error filter; Multi-resolution image processing: wavelet transform in one and two dimensions, tree structured wavelet transform, pyramid structured wavelet transform, curvelet transform; Morphological image processing: erosion, dilation, opening, closing, hole filling, connected components, thinning, skeletons, extension of morphological operations to gray scale images; Image segmentation: thresholding, region based segmentation, contour based segmentation, graph based segmentation; Color image processing: color models and transformations, edge detection and segmentation in color images, color image compression; Digital image security; Image content feature extraction, representation and image retrieval; Concept learning and object recognition.

Introduction; Molecular biology basics: DNA, RNA, genes, and proteins; Restriction mapping algorithm; Motif in DNA sequences, motif finding algorithms; Genome rearrangements, sorting by reversals and breakpoints; DNA sequence alignments; Gene prediction; Space-efficient sequence alignments, sub-quadratic alignment; DNA sequencing, genome sequencing, protein sequencing, spectrum graphs; Combinatorial pattern matching: Exact pattern matching, heuristic similarity search algorithms, approximate string matching, BLAST, FASTA; Clustering: Microarrays, hierarchical clustering, K-means clustering, corrupted cliques problem, CAST clustering algorithm; Evolutionary trees.

Modern programming languages; Object oriented programming systems; Runtime virtual machines: How virtual machine works, Different classes of virtual machines, Jikes research virtual machine; Compilation techniques: Interpreter and baseline compilation, Just-in-time compilation and dynamic optimization; Type systems: Strong and weak type systems, Static and dynamic type checking; Concurrency and synchronization: Atomic operations, Thin locks and lock free design; Memory model; Thread scheduling; Dynamic memory allocation: Free-list, contiguous and region based allocation, Fast parallel memory allocation; Garbage collection: Fundamental garbage collection algorithms, Stop-the-world, parallel and concurrent garbage collection, State of the art garbage collectors; Performance analysis and benchmarking.