YOLO8 Expansion -- 3
Budget: $250 – $750 USD
I'm looking for a skilled deep learning expert to enhance the YOLO8 structure with new layers like Efficient Channel Attention (ECA), Large Separable Kernel Attention (LSK), ParNet Attention (ParNet), and Shuffle Attention (Shuffle) for the purpose of improving object detection accuracy.
Key Responsibilities:
- Implementing the YOLO8 structure
- Integrating the new layers (ECA, LSK, ParNet, Shuffle) in the YOLO8 network
- Ensuring the new layers effectively enhance the object detection accuracy
Ideal Skills and Experience:
- Deep understanding of object detection models, particularly YOLO
- Experience with integrating attention mechanisms like ECA, LSK, ParNet, and Shuffle
- Strong experience in improving model accuracy
- Good understanding of deployment on desktop computers
This project is perfect for someone who's not only a PyTorch expert but can also innovate with different layer additions. The YOLO8 network needs to perform effectively with these new enhancements to meet our accuracy goals.
Key Responsibilities:
- Implementing the YOLO8 structure
- Integrating the new layers (ECA, LSK, ParNet, Shuffle) in the YOLO8 network
- Ensuring the new layers effectively enhance the object detection accuracy
Ideal Skills and Experience:
- Deep understanding of object detection models, particularly YOLO
- Experience with integrating attention mechanisms like ECA, LSK, ParNet, and Shuffle
- Strong experience in improving model accuracy
- Good understanding of deployment on desktop computers
This project is perfect for someone who's not only a PyTorch expert but can also innovate with different layer additions. The YOLO8 network needs to perform effectively with these new enhancements to meet our accuracy goals.