01CF114 Adaptive Media Processing

1.0 Credits, 1, 2 Year, SprAB Mon2
Keisuke Kameyama

Course Overview

Adaptive techniques in processing, recognition and retrieval of media information will be discussed. Much weight will be put on (re-)assuring the fundamental knowledge and algorithms in machine learning and signal/image processing, that are essential for adaptive handling of media contents. In addition, up-to-date methods in the field will also be mentioned. (Lecture in English)

Remarks

Identical to 01CH609 and 0AL5430.
Lectures are conducted in English.

Course Type

lectures

Relation to Degree Program Competences

Knowledge Utilization Skills,International Skills,Research Skills,Expert Knowledge

Course Objectives(Learning Outcomes)

Understanding of recent techniques of pattern recognition and machine learning to deal with media, especially recognition and processing of images.

Course Keywords

Pattern Recognition, Adaptation, Feature Extraction, Image Processing, machine learning

Class Schedule

Course Prerequisites

Basic knowledge on Linear Algebra, Analysis, Probability and Statistics of undergraduate level. Understanding of basic signal processing would be a plus.

Grading Philosophy

Irregular small assignments and final term paper will be evaluated.

Course Hours Breakdown and Out-of-Class Learning

Textbooks, References,and Supplementary Materials

Office Hours and Contact Information

Other(Behavioral expectations and points to note for students during coursework)

Lecture will be given in English. Submissions must be made in English.

Relation to Other Courses

Teaching Fellow and/or Teaching Assistant

None