Project Image Processing / Pattern Recognition
PDF Course Catalog Deutsche Version: BV3
Version: 1 | Last Change: 16.09.2019 10:19 | Draft: 0 | Status: vom verantwortlichen Dozent freigegeben
Long name | Project Image Processing / Pattern Recognition |
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Approving CModule | BV3_BaMT |
Responsible |
Prof. Dr. Dietmar Kunz
Professor Fakultät IME im Ruhestand |
Valid from | summer semester 2023 |
Level | Bachelor |
Semester in the year | summer semester |
Duration | Semester |
Hours in self-study | 162 |
ECTS | 6 |
Professors |
Prof. Dr. Dietmar Kunz
Professor Fakultät IME im RuhestandProf. Dr. Lothar Thieling Professor Fakultät IME |
Requirements | Module Image Processing Module Pattern Recognition |
Language | English |
Separate final exam | No |
Burger/Burge: Digitale Bildverarbeitung |
Gonzales/Woods: Digital Image Processing |
Goal type | Description |
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Knowledge | problem specific methods resulting from system model and literature search |
Skills | skilled use of software development environment |
Skills | skilled use of tools for image processing and image analysis |
Skills | if required: skilled use of tools for training neural networks |
Skills | understanding of scientific texts in English |
Skills | presentation of project results in English |
Skills | accomplish complex tasks in teams |
Skills | present project results |
Skills | Derive complex problem solutions that can be implemented using image processing and image analysis analyse and understand complex problems derive system behaviour from specifying texts analyse systems model system from subsystems model, implement, and test subsystems map subsystems as far as possible on available components (image processing modules), i.e. selection of models and parameters implement and test required but not available image processing modules in C or Java using software development environment implement, test, and validate entire system (problem solution) Derive problem solution as chain of algorithms using image processing modules parametrize image processing modules test and validate solution iteratively improve algorithmic chain |
Type | Attendance (h/Wk.) |
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Project | 1 |
Tutorial (voluntary) | 0 |
none |
Accompanying material | development environment for image processing and image analysis (ImageJ, IBV-Studio), electronic collection of sample programs and sample applications, electronic development environmentfor dreation and training of neural networks |
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Separate exam | Yes |
Exam Type | EN Projektaufgabe im Team bearbeiten (z.B. im Praktikum) |
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Details | Presenation and documentation of project progress including oral project presentation at mile stone meetings. Final report. |
Minimum standard | Project has to be processed with adequate effort and the achieved results must be visible from the presentations and documentation. |
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