Deep Learning and Yolov2 for Object Classification

Capture images of oranges and apples and apply deep-learning techniques to classify them for robotic tasks.
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Aktualisiert 15. Jun 2024

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Intelligent Control Systems by Asst. Prof. Dr. Claudia F. Yaşar
This repository contains the curriculum materials used for the Intelligent Control Systems course YTU Department of Control and Automation Engineering.
Deep-Learning-with-Yolov2-for-Object-Classification
We explore machine learning for image classification, using a camera to capture and classify images of objects like oranges and apples. This demonstrates how classification models can enhance pick-and-place operations in industrial robots, showcasing practical applications of machine learning in automating industrial processes.
Important! All the required files are shared using MATLAB Drive. upload all these files to your MATLAB current folder
Deep Learning Implementation with Yolov2 for Object Detection
Acknowledgements
I would like to express my gratitude to the students of the Intelligent Control Systems course of the YTÜ Control and Automation Engineering department, Class 2022 and 2023, whose dedication and hard work made this project possible. I am also deeply thankful to our Control Tech LAB team, Doctors Marco Rossi, and Melda Ulusoy for their invaluable contributions.

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Claudia Fernanda Yasar (2024). Deep Learning and Yolov2 for Object Classification (https://www.mathworks.com/matlabcentral/fileexchange/168121-deep-learning-and-yolov2-for-object-classification), MATLAB Central File Exchange. Abgerufen.

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Version Veröffentlicht Versionshinweise
1.0.0