positive666/yolo_research
Research repository for YOLO object detection models (v5/v7/v8) with Swin Transformer and Attention mechanisms integrated.
Not currently ranked — collecting fresh signals.
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This repository provides implementations and improvements for YOLO-based object detection models including YOLOv5, YOLOv7, and YOLOv8. It incorporates Swin Transformer V2 and various attention mechanisms into the detection pipelines. The project supports multiple vision tasks including detection, pose estimation, classification, and segmentation. It includes training utilities, custom network architecture modifications, and deployment tools for engineering applications.
Frequently asked
- What is positive666/yolo_research?
- Research repository for YOLO object detection models (v5/v7/v8) with Swin Transformer and Attention mechanisms integrated.
- Is yolo_research open source?
- Yes — positive666/yolo_research is open source, released under the GPL-3.0 license.
- What language is yolo_research written in?
- positive666/yolo_research is primarily written in Python.
- How popular is yolo_research?
- positive666/yolo_research has 667 stars on GitHub.
- Where can I find yolo_research?
- positive666/yolo_research is on GitHub at https://github.com/positive666/yolo_research.