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|  '''Betreuer''': || [[Benutzer:Ulrich_Schneider| Prof. Dr.-Ing. Schneider]]
|  '''Betreuer''': || [[Benutzer:Ulrich_Schneider| Prof. Dr.-Ing. Schneider]]
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|  '''Zweitprüfer''': || Mirek Göbel
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|}
{|  
{|  
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! # !! Categorie !! Grader Lecture
! # !! Categorie !! Grader Lecture
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| 1 || Recovery and restoration of information || 5
| 1 || [[Image Processing: Recovery and restoration of information|Recovery and restoration of information]] || 5
|-
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| 2 || Image enhancement || 6
| 2 || [[Image Processing: Image enhancement|Image enhancement]] || 6
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| 3|| Noise Reduction || 7
| 3|| [[Image Processing: Noise Reduction|Noise Reduction]] || 7
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| 4|| Data based segmentation || 8
| 4|| [[Image Processing: Data based segmentation|Data based segmentation]] || 8
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| 5|| Model based segmentation || 9
| 5|| [[Image Processing: Model based segmentation|Model based segmentation]] || 9
|-
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| 6|| Classification || 10
| 6|| [[Image Processing: Classification|Classification]] || 10
|}
|}


'''SVN Repository:'''<br>
'''SVN Repository:'''<br>
  https://svn.hshl.de/svn/MATLAB_Vorkurs/trunk/Signalverarbeitung_mit_Kuenstlicher_Intelligenz
  https://svn.hshl.de/svn/MATLAB_Vorkurs/trunk/Signalverarbeitung_mit_Kuenstlicher_Intelligenz
== Requirements regarding the Scientific Methodology ==
* Scientific methodology (project plan, etc.), helpful article: [[Gantt-Diagramm| Gantt Diagramm erstellen]]
* Weekly progress reports (informative), update the [[Diskussion:Image Processing with MATLAB and AI|Meeting Minutes]]
* Project presentation in the wiki
* Daily backup of work results in  [[Software_Versionsverwaltung_mit_SVN|SVN]]
*[[Studentische_Arbeiten_bei_Prof._Schneider|Student Projects with Prof. Schneider]]
*[[Anforderungen_an_eine_wissenschaftlich_Arbeit| Anforderungen an eine wissenschaftlich Arbeit]]


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→ zurück zum Hauptartikel: [[Offene_Themen_von_Prof._Schneider| Studentische Arbeiten]]
→ zurück zum Hauptartikel: [[Offene_Themen_von_Prof._Schneider| Requirements for a scientific project]]

Aktuelle Version vom 20. Januar 2026, 10:47 Uhr

Abb. 1: Signalverarbeitung mit MATLAB® und Künstlicher Intelligenz
Autor: Ajay Paul
Art: bachelor thesis
Starttermin: TBD
Abgabetermin: TBD
Betreuer: Prof. Dr.-Ing. Schneider
Zweitprüfer: Mirek Göbel

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

  1. Solve the Image Processing Tasks with classic algorithms.
  2. Research on AI Solutions.
  3. Evaluation of the solutions using a morphological box (Zwicky box)
  4. Solve the Image Processing Tasks with AI algorithms.
  5. Compare the different approaches according to scientific criteria
  6. Scientific documentation

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.
  • Use MATLAB R2025b for the algorithms.
Table 1: Image Processing Categories
# 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

SVN Repository:

https://svn.hshl.de/svn/MATLAB_Vorkurs/trunk/Signalverarbeitung_mit_Kuenstlicher_Intelligenz

Requirements regarding the Scientific Methodology


→ zurück zum Hauptartikel: Requirements for a scientific project