Project description
Detex 2.0 leverages artificial intelligence and high-resolution cameras to aid the sorting process in textile recycling. By optimizing the classification of clothing items and enhancing contamination detection, it enables more efficient processing of used textiles.
The "detex 2.0" project aims to support the sorting process in textile recycling. By utilizing artificial intelligence and high-resolution cameras, important features of clothing items are captured and categorized. The team has optimized the classification of clothing items across nine classes and improved contamination detection through individual labeling and training of a YOLO model. Transitioning to the YOLOv8 algorithm and expanding contamination detection has led to significant improvements. The models were trained using over 50,000 images of clothing items generated to be nearly lifelike.
- Here is the Showcase Website for more information.
Supervisor:
Phone: | +49 821 5586-3512 |
Phone: | +49 821 5586-3050 |
Students:
Tobias Weichseldorfer
Jannik Hilmer
Martin Kohnle
Daniel Beck
Matthias Müller
Semir Canbolat