Diskussion:Image Processing with MATLAB and AI - Versionsgeschichte

Ajay.paul@stud.hshl.de am 14. April 2026 um 13:11 Uhr

2026-04-14T13:11:13Z

← Nächstältere Version		Version vom 14. April 2026, 13:11 Uhr
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	* Investigated and summarized the key differences		* Investigated and summarized the key differences
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	\| 15 \|\| 06.03.2026 \|\|		\| 15 \|\| 06.04.2026 \|\|
	* Evaluation of Deep Learning Architectures for Image Processing using A Morphological Box Analysis in MATLAB		* Evaluation of Deep Learning Architectures for Image Processing using A Morphological Box Analysis in MATLAB
	** Used Zwicky Box Analysis		** Used Zwicky Box Analysis
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			* Did evaluation on deep learning architectures and created Morphological Box Analysis
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			\| 16 \|\| 13.04.2026 \|\|
	* Develop Deep learning models for image processing		* Develop Deep learning models for image processing
	** use pertained models for the image processing		** use pertained models for the image processing

2026-04-14T13:05:02Z

← Nächstältere Version		Version vom 14. April 2026, 13:05 Uhr
Zeile 98:		Zeile 98:
	** Suitability for edge devices		** Suitability for edge devices
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	* ~~Did the research to identify~~ the key ~~difference~~		*
			* Analyzed and identified the key differences
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	\| 13 \|\| 23.03.2026 \|\|		\| 13 \|\| 23.03.2026 \|\|
Zeile 107:		Zeile 108:
	** Suitability for edge devices		** Suitability for edge devices
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	* ~~Did the research~~ to ~~identify the~~ key ~~difference~~		* Conducted a comparative analysis to highlight key differences
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	\| 14 \|\| 30.03.2026 \|\|		\| 14 \|\| 30.03.2026 \|\|
Zeile 116:		Zeile 117:
	** Suitability for edge devices		** Suitability for edge devices
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	* ~~Did the research to identify~~ the key ~~difference~~		* Investigated and summarized the key differences
	\|-		\|-
	\| 15 \|\| 06.03.2026 \|\|		\| 15 \|\| 06.03.2026 \|\|

2026-04-08T08:51:40Z

@@ Zeile 82: / Zeile 82: @@
 |-
 | 11 || 09.03.2026 ||
-* Identify key differences in:
+* Identify key differences in: ResNet
 ** Model architecture
 ** Computational complexity
 ** Accuracy and performance
 ** Suitability for edge devices
-* Prepare a comparison table for ResNet, MobileNetV2, EfficientNet, and Vision Transformers
+||
 ||
 * To do
 |}

2026-03-10T16:12:17Z

@@ Zeile 80: / Zeile 80: @@
 ** EfficientNet (Scalability)
 ** Vision Transformers (ViT
 |}

2026-03-10T16:03:21Z

← Nächstältere Version		Version vom 10. März 2026, 16:03 Uhr
Zeile 75:		Zeile 75:
	** Vision Transformers (ViT)		** Vision Transformers (ViT)
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	* ~~[To Do] Review~~ key literature for selected architectures.		* Reviewed key literature for selected architectures.
	* ~~[To Do] Create a comparison matrix~~ (~~Accuracy vs. Parameters vs. Speed~~).		** ResNet (Standard)
	* ~~[To Do] Draft the "State of the Art" chapter justifying the choice of YOLO/CNN over these architectures.~~		** MobileNetV2 (Edge Efficiency)
			** EfficientNet (Scalability)
			** Vision Transformers (ViT
	\|}		\|}

2026-02-25T18:34:08Z

@@ Zeile 66: / Zeile 66: @@
 * Trained the model on the custom LEGO dataset.
 * Successfully ran inference: The system automatically identifies and classifies LEGO bricks in new images.
 |}

2026-02-24T07:23:13Z

@@ Zeile 1: / Zeile 1: @@
 {| class="wikitable"
 |-
-! #   !! date  !!  planning for the week!! progress
+! #   !! Date  !!  Planning for the week !! Progress
 |-
-| 1  || 20.01.2026  ||
+| 1  || 01.01.2026  ||
-* Please plan your bachelor thesis with a Gantt-chart
+* Plan bachelor thesis with Gantt-chart.
-* Document your Progress in this wiki article.
+* Register to MATLAB Grader.
-* Write a weekly progress report.
+* Understand requirements and set up SVN.
 ||
-*please fill out
+* Created Gantt chart (Timeline: Jan–Apr).
+* Analyzed requirements and set up development environment.
 |}

2026-01-20T09:46:13Z

← Nächstältere Version		Version vom 20. Januar 2026, 09:46 Uhr
Zeile 9:		Zeile 9:
	* Write a wiki sub-article for every task.		* Write a wiki sub-article for every task.
	* Register to the image processing class in MATLAB Grader.		* Register to the image processing class in MATLAB Grader.
	* Solve the Image Processing Tasks with classic algorithms.		* Solve the Image Processing Tasks with classic algorithms in MATLAB.
			* Save the results to <code>https://svn.hshl.de/svn/MATLAB_Vorkurs/trunk/Signalverarbeitung_mit_Kuenstlicher_Intelligenz/mFiles</code>
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	*please fill out		*please fill out

	\|}		\|}

2026-01-20T09:45:16Z

← Nächstältere Version		Version vom 20. Januar 2026, 09:45 Uhr
Zeile 8:		Zeile 8:
	* Write a weekly progress report.		* Write a weekly progress report.
	* Write a wiki sub-article for every task.		* Write a wiki sub-article for every task.
			* Register to the image processing class in MATLAB Grader.
	* Solve the Image Processing Tasks with classic algorithms.		* Solve the Image Processing Tasks with classic algorithms.

	\|\|		\|\|
	*please fill out		*please fill out

	\|}		\|}

2026-01-20T09:44:33Z

← Nächstältere Version		Version vom 20. Januar 2026, 09:44 Uhr
Zeile 8:		Zeile 8:
	* Write a weekly progress report.		* Write a weekly progress report.
	* Write a wiki sub-article for every task.		* Write a wiki sub-article for every task.
			* Solve the Image Processing Tasks with classic algorithms.
	\|\|		\|\|
	*please fill out		*please fill out

	\|}		\|}