| | --- |
| | license: gpl-3.0 |
| | datasets: |
| | - detection-datasets/coco |
| | --- |
| | |
| | # Introduction |
| |
|
| | This repository stores the model for YOLOv9-T, compatible with Kalray's neural network API. </br> |
| | Please see www.github.com/kalray/kann-models-zoo for details and proper usage. </br> |
| |
|
| | # Contents |
| |
|
| | - ONNX: yolov9t.optimized.onnx |
| |
|
| | # Lecture note reference |
| |
|
| |
|
| | # Repository or links references |
| |
|
| | - repository: https://github.com/WongKinYiu/yolov9 |
| | - weights: https://github.com/WongKinYiu/yolov9/releases/download/v0.1/yolov9-t-converted.pt |
| |
|
| |
|
| | BibTeX entry and citation info |
| | ``` |
| | @article{wang2024yolov9, |
| | title={{YOLOv9}: Learning What You Want to Learn Using Programmable Gradient Information}, |
| | author={Wang, Chien-Yao and Liao, Hong-Yuan Mark}, |
| | booktitle={arXiv preprint arXiv:2402.13616}, |
| | year={2024} |
| | } |
| | |
| | @article{chang2023yolor, |
| | title={{YOLOR}-Based Multi-Task Learning}, |
| | author={Chang, Hung-Shuo and Wang, Chien-Yao and Wang, Richard Robert and Chou, Gene and Liao, Hong-Yuan Mark}, |
| | journal={arXiv preprint arXiv:2309.16921}, |
| | year={2023} |
| | } |
| | ``` |
