Course Catalog 2008-2009
Basic

Basic Pori International Postgraduate Open University

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Course Catalog 2008-2009

TTE-5606 Machine Vision: Advanced Topics, 5 cr

CourseĀ“s person responsible

Reijo Tuokko, Timo Prusi

Implementations

  Lecture times and places Target group recommended to
Implementation 1   DI-Opiskelijat
Jatko-opiskelijat
KV-opiskelijat  


Requirements

Accepted laboratory assignments, acceptably returned and presented seminar work, sufficient participation to seminars. Exam.
Completion parts must belong to the same implementation

Principles and baselines related to teaching and learning

-

Objectives

The course provides deeper knowledge about machine vision topics specialized to production automation, microproduction, microfactories, and laser processes.

Content

Content Core content Complementary knowledge Specialist knowledge
1. Topics discussed on the course vary from year to year.     


Evaluation criteria for the course

Seminar(s) and assignments are mandatory part of the course. They will also be graded and they give roughly half of the total course grade. The rest of the total course grade comes from the exam.

Assessment scale:

Numerical evaluation scale (1-5) will be used on the course

Partial passing:

Completion parts must belong to the same implementation

Study material

Type Name Author ISBN URL Edition, availability, ... Examination material Language
Lecture slides   Machine Vision: Advanced Topics   Lecturers            English  
Other literature   Scientific papers supporting the topics   N.N.            English  


Prerequisites

Course O/R
OHJ-1106 Programming I Recommended  
TTE-5216 Machine Vision in Production Automation Recommended  

Prerequisite relations (Requires logging in to POP)

More precise information per implementation

  Description Methods of instruction Implementation
Implementation 1 Implementation for academic year 2008 - 2009.   Lectures
Seminar work
ITC Utilization
Laboratory assignments
   
Contact teaching: 20 %
Distance learning: 20 %
Self-directed learning: 60 %  


Last modified11.08.2008
ModifierTimo Prusi