Image Processing with MATLAB and AI: Unterschied zwischen den Versionen
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= Getting startes = | = Getting startes = | ||
* You are invited to the image processing class in [https://grader.mathworks.com/courses/169570-image-processing-with-matlab MATLAB Grader]. | * You are invited to the image processing class in [https://grader.mathworks.com/courses/169570-image-processing-with-matlab MATLAB Grader]. | ||
* Choose the examples from the categories in table 1. | * Choose the examples from the categories in table 1. Start with 1 end with 6. | ||
* Solve the tasks with classic algorithms. | * Solve the tasks with classic algorithms. | ||
* Solve the tasks with AI. | * Solve the tasks with AI. | ||
Version vom 11. Oktober 2025, 09:08 Uhr

| Autor: | Ajay Paul |
| Art: | bachelor thesis |
| Starttermin: | TBD |
| Abgabetermin: | TBD |
| Betreuer: | Prof. Dr.-Ing. Schneider |
Introduction
Signal processing has long been a basis in the analysis and manipulation of data in various domains such as telecommunications, radar, audio processing, and imaging. Signal processing has traditionally focused on analyzing, filtering, and interpreting signals in both the time and frequency domains. With the integration of AI, especially deep learning, the possibilities expand to include noise reduction and more. It is essential in many modern applications such as communications, audio and image processing, biomedical signal analysis, and control systems.
Task list
- Solve the Image Processing Tasks with classic algorithms.
- Research on AI Solutions.
- Solve the Image Processing Tasks with AI algorithms.
- Compare the two approaches according to scientific criteria
- scientific documentation in
Getting startes
- You are invited to the image processing class in MATLAB Grader.
- Choose the examples from the categories in table 1. Start with 1 end with 6.
- Solve the tasks with classic algorithms.
- Solve the tasks with AI.
- Save your results in SVN.
| # | Categorie | Grader Lecture |
|---|---|---|
| 1 | Recovery and restoration of information | 5 |
| 2 | Image enhancement | 6 |
| 3 | Noise Reduction | 7 |
| 4 | Data based segmentation | 8 |
| 5 | Model based segmentation | 9 |
| 6 | Classification | 10 |
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