The Pattern Recognition Techniques objectives are related with the design and implementation of algorithms emulating the human ability to recognize patterns. Since early times of computing this has been found the most intriguing and challenging task. Pattern Recognition (PR) is the scientific discipline that studies the operation and design of systems that recognize patterns in data. Important application areas in Computer Science are:
Facial Expression Detection;
Vehicle Trajectory Recognition;
Handwriting Character Recognition;
Pattern Mining in the WEB (WWW, DataWarehouses, Business Intelligence, etc.);
Biomedical Data Mining
The course will give the techniques able to explore many of the above applications, and the general analytical models able to cope with real world data.
Pattern Recognition: Concepts, Methods and Applications.
2.Statistical Approaches (Linear Discriminants, Fisher, Naïve-Bayes, Maximum à Posteriori (MAP) etc.;
3.Neural Networks (supervised and non-supervised)*;
. Competence in analysis and synthesis; . Computer Skills for the scope of the study; . Competence to solve problems; . Capacity of decision; . Critical thinking; . Competence in oral and written communication; . Adaptability to new situations; . Creativity; . Competence in applying theoretical knowledge in practice; . Research skills; (by decreasing order of importance)
Teaching hours per semester
total of teaching hours
Sseminar or study visit
assessment implementation in 20122013 Assessment Report of a seminar or field trip: 25.0% Project: 35.0% Exam: 40.0%
Bibliography of reference
Marques de Sá, J.P.(2001), Pattern Recognition: Concepts, Methods and Applications, Springer-Verlag.
Theoretical classes with detailed presentation, using audiovisual means, of the concepts, principles and fundamental theories and solving of basic practical exercises to illustrate the practical interest of the subject and exemplify its application to real cases.
Theoretical-practical classes where the students, supervised by the staff member, solve practical exercises, which require the combination of different theoretical concepts and promote critical reasoning in the presence of more complex problems.