TIF3212-Pattern Recognition
Lecturer : Shofwatul ‘Uyun
Email : shofwatul.uyun@uin-suka.ac.id; shofwa_uyun@yahoo.com; shofwa.uyun@gmail.com
Office: the second floor of saintek building
Office Hours: Tuesday 10:30-12:00 am, Thursday 1-2 pm, or by appointment
Website : shofwatuluyun.com
Staff Mailing List: dosentif-uinsuka@yahoogroups.com
Thursday (09-11:50 am) Location : 409;
Prerequisites : artificial Intelligence
Grading and grading policy
The final grade will be based on :
- Midterm exam (25%)
- Final exam (25%).
- Project/Group assignments (15%)
- Paper presentation (15%)
- Final Project (20%)
References :
- Duda, Richard O., Peter E. Hart, and David G. Stork. Pattern classification. 2nd ed. New York, NY: Wiley, 2001. ISBN: 0471056693.
- Mallot, Hanspeter A. Computational Vision: Information Processing in Perception and Visual Behavior. Translated by John S. Allen. Cambridge, MA: MIT Press, 2000. ISBN: 0262133814.
- Forsyth, David A., and Jean Ponce. Computer Vision: a Modern Approach. Upper Saddle River, NJ: Prentice Hall, 2003. ISBN: 0130851981.
- Hastie, Trevor, Robert Tibshirani, and Jerome Friedman. The Elements of Statistical Learning: Data Mining, Inference, and Prediction: with 200 full-color illustrations. New York, NY: Springer, c2001. ISBN: 0387952845.
Topics :
- Overview of problems of machine vision and pattern classification
- Image formation and processing
- Feature extraction from images
- Biological object recognition
- Bayesian Decision Theory
- Clustering
- Classification
Materials of pattern recognition :
- Overview [pdf]
- Feature Extraction [pdf]
- Classification Method (Supervised) [pdf]
- Learning Vector Quantification [winzip]
- Support vector Machine-1 [winzip]
- Support vector Machine-2 [winzip]
- Fuzzy C-Means Clustering [pdf]
- Example of Fuzzy C-Means Clustering [pdf]
- Substractive Clustering [pdf]
- Example of Substractive Clustering [pdf]