| --- |
| license: mit |
| tags: |
| - computer-vision |
| - object-detection |
| - e-waste |
| - yolo |
| - industrial |
| - annotated-images |
| - deep-learning |
| dataset_name: ewaste-yolo-classification |
| --- |
| |
| # E-Waste YOLO Classification Dataset |
|
|
| **Dataset Summary** |
|
|
| This dataset contains annotated images of electronic waste (e-waste) items for object detection tasks. It was curated to support training and evaluation of YOLO-based deep learning models for automated e-waste identification and classification. |
|
|
| ## ☁️ Dataset Overview |
|
|
| | Feature | Details | |
| |---------|---------| |
| | **Task** | Object Detection | |
| | **Modalities** | Images, Annotations | |
| | **Annotation Format** | YOLO / COCO compatible | |
| | **License** | MIT | |
| | **Categories** | Batteries, Circuit Boards, LCDs, Resistors, Capacitors, Regulators, IoT Sensors, etc. | |
|
|
| ## 📄 Paper Reference |
|
|
| If you use this dataset, please cite: |
|
|
| > Rajeev, P. A., Dharewa, V., Lakshmi, D., Vishnuvarthanan, G., Giri, J., Sathish, T., & Alrashoud, M. (2025). *Advancing e-waste classification with customizable YOLO based deep learning models.* Scientific Reports, 15, 18151. https://doi.org/10.1038/s41598-025-94772-x |
|
|
| ### 📚 BibTeX |
| ```bibtex |
| @article{rajeev2025advancing, |
| title={Advancing e-waste classification with customizable YOLO based deep learning models}, |
| author={Rajeev, P. Akhil and Dharewa, Vivek and Lakshmi, D. and Vishnuvarthanan, G. and Giri, J. and Sathish, T. and Alrashoud, M.}, |
| journal={Scientific Reports}, |
| volume={15}, |
| pages={18151}, |
| year={2025}, |
| doi={10.1038/s41598-025-94772-x} |
| } |
| |
| |
