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College of Engineering & Technology  Alexandria
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Image Processing & Pattern Recognition

  • Computer Engineering |

Description

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Program

Bachelor Degree in Computer Engineering

Objectives

  • In the field of pattern recognition the aim is to teach a computer to recognize patterns in data sets (e.g. input-output relations). Real data is often noisy, and therefore probabilistic methods are used. Using the Bayesian perspective is the starting point for a treatment of both classical methods (least mean squares methods, discriminant analysis) and modern methods (neural networks, Bayesian learning).

Textbook

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Course Content

content serial Description
1Week Number 1 : Introduction to Pattern Recognition.
2Week Number 2 : Gray scale Transformations.
3Week Number 3 : Smoothing Transformations.
4Week Number 4 : Edge Detection.
5Week Number 5 : Scene Segmentation and labeling.
6Week Number 6 : Shape Detection.
7Week Number 7 : 7th week exam + Revision.
8Week Number 8 : Morphological Operations.
9Week Number 9 : Statistical Decision Making.
10Week Number 10 : Minimization of Classification Error.
11Week Number 11 : Hierarchical Clustering.
12Week Number 12 : 12th week exam + Revision.
13Week Number 13 : Partitioned Clustering.
14Week Number 14 : Feed Forward Neural Networks.
15Week Number 15 : Hopfield Networks.
16Week Number 16 : Presentation of projects and Final Exam.
1Week Number 1 : Introduction to Pattern Recognition.
2Week Number 2 : Gray scale Transformations.
3Week Number 3 : Smoothing Transformations.
4Week Number 4 : Edge Detection.
5Week Number 5 : Scene Segmentation and labeling.
6Week Number 6 : Shape Detection.
7Week Number 7 : 7th week exam + Revision.
8Week Number 8 : Morphological Operations.
9Week Number 9 : Statistical Decision Making.
10Week Number 10 : Minimization of Classification Error.
11Week Number 11 : Hierarchical Clustering.
12Week Number 12 : 12th week exam + Revision.
13Week Number 13 : Partitioned Clustering.
14Week Number 14 : Feed Forward Neural Networks.
15Week Number 15 : Hopfield Networks.
16Week Number 16 : Presentation of projects and Final Exam.
1Week Number 1 : Introduction to Pattern Recognition.
2Week Number 2 : Gray scale Transformations.
3Week Number 3 : Smoothing Transformations.
4Week Number 4 : Edge Detection.
5Week Number 5 : Scene Segmentation and labeling.
6Week Number 6 : Shape Detection.
7Week Number 7 : 7th week exam + Revision.
8Week Number 8 : Morphological Operations.
9Week Number 9 : Statistical Decision Making.
10Week Number 10 : Minimization of Classification Error.
11Week Number 11 : Hierarchical Clustering.
12Week Number 12 : 12th week exam + Revision.
13Week Number 13 : Partitioned Clustering.
14Week Number 14 : Feed Forward Neural Networks.
15Week Number 15 : Hopfield Networks.
16Week Number 16 : Presentation of projects and Final Exam.
1Week Number 1 : Introduction to Pattern Recognition.
2Week Number 2 : Gray scale Transformations.
3Week Number 3 : Smoothing Transformations.
4Week Number 4 : Edge Detection.
5Week Number 5 : Scene Segmentation and labeling.
6Week Number 6 : Shape Detection.
7Week Number 7 : 7th week exam + Revision.
8Week Number 8 : Morphological Operations.
9Week Number 9 : Statistical Decision Making.
10Week Number 10 : Minimization of Classification Error.
11Week Number 11 : Hierarchical Clustering.
12Week Number 12 : 12th week exam + Revision.
13Week Number 13 : Partitioned Clustering.
14Week Number 14 : Feed Forward Neural Networks.
15Week Number 15 : Hopfield Networks.
16Week Number 16 : Presentation of projects and Final Exam.

Markets and Career

  • Generation, transmission, distribution and utilization of electrical power for public and private sectors to secure both continuous and emergency demands.
  • Electrical power feeding for civil and military marine and aviation utilities.
  • Electrical works in construction engineering.
Courses
  • Degree Bachelor
  • Code: CC516
  • Credit hrs: 3
  • Prequisites:
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