| Course Code |
Course Name |
Credit |
| CSE 563 |
Computer Vision |
(3+0+0) 3 |
| Image formation. Early processing: low-level vision and feature extraction. Boundary detection. Region growing. Texture. Motion. Two-dimensional and three-dimensional representation. High-level vision: learning and matching.. |
| CSE 565 |
Artificial Neural Networks |
(3+0+0) 3 |
| Introduction to cognitive science. Parallel, distributed problems. Constraint satisfaction. Hopfield model. Supervised and unsupervised learning. Single and multi-layer perceptrons. Static and dynamic network architecture. Comparison of neural approaches with parametric and nonparametric statistical methods. Neural network applications.. |
| CSE 566 |
Machine Learning |
(3+0+0) 3 |
| Paradigms and issues of machine learning. Theory and methodology of induction. Instance-based learning. Genetic algorithms, genetic-based machine learning, classifier systems. Learning decision trees. Explanation-based learning. Discovery systems. Learning problem solving strategies. |
| CSE 567 |
Image Processing |
(3+0+0) 3 |
| Mathematical model of an image. Frequency spectrum of an image. Sampling of an image, aliasing and conditions on sampling frequency. Separability in 2-D signals. Periodicity concept in an image. Expansion of an image into Fourier series. Construction of an image from its harmonics. The 2-D Fourier transform. The Fourier transform of separable images. The z-transform and transfer function. The linear operations applied to an image: convolution, mask and impulse response. 2-D FIR filters and IIR filters. Methods of image enhancement. Image segmentation. Image restoration and compression. Cellular neural networks and their applications in 2-D filtering. Recognition and interpretation. |
| CSE 572 |
Cryptography |
(3+0+0) 3 |
| Introduction to cryptography, classical ciphers, block ciphers, DES, AES, modes of operation, stream ciphers, PRNG, LFSR, randomness tests, public key cryptography, RSA, DH, digital signatures, authentication protocols, key exchange, hash functions, elliptic curves. |
| CSE 581-589 |
CSE Special Topics in Computer Engineering I-IX |
(3+0+0) 3 |
| Study of special topics chosen among the recent technological or theoretical developments in computer engineering. |
| CSE 640 |
Advanced Topics in Parallel and Distributed Computing |
(3+0+0) 3 |
| Parallel methods for computations in the areas of bioinformatics, computational physics, and other disciplines. Parallel algorithms. Topics in distributed computing. Parallel and distributed computing architectures. |
| CSE 645 |
Computer Performance Evaluation |
(3+0+0) 3 |
| Introduction to computer performance measurement and evaluation. Job processing models. Queuing Theory. Simulation techniques. Systems analysis techniques. Estimating CPU performance. Programmed measurement techniques. |
| CSE 661 |
Advanced Natural Language Processing |
(3+0+0) 3 |
| Levels of natural language processing: morphological, syntactic and semantic analysis. Transformational grammars. Affix grammars and 2-level representation and processing. Meaning and interpretation. Applications: intelligent interfaces, text processing aids, machine translation, natural language understanding. Transition networks and ATN parsing. |
| CSE 664 |
Computer Speech Processing |
(3+0+0) 3 |
| Man-machine communication. Speech models and representations. Speech synthesis. Speech coding. Speech recognition. Dynamic time warping and hidden Markow models. Neural networks for speech processing. Speech enhancement. |
| CSE 681-689 |
Special Studies in Computer Engineering |
(3+0+0) 3 |
| Study of current research topics in computer engineering by Ph.D. students under the guidance of a faculty member and presentation of the chosen topic. |
| CSE 690 |
Ph.D. Thesis |
Non- Credit |
| Preparation of a Ph.D. thesis under the guidance of an academic advisor. |
Course Description
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