Enhance Semantic Segmentation Model Performance on Cityscapes
Budget: $30 – $250 USD
I’m seeking a freelancer to enhance my TensorFlow-based semantic segmentation model on the Cityscapes dataset. The current mIoU is ~40%; the goal is at least 80% mIoU using a novel and lightweight architecture (≤ 1M parameters).
Requirements:
- Experience in hyperparameter tuning, data augmentation, and fine-tuning.
- Access to a GPU or high-performance computing resources.
Responsibilities:
- Design a novel, lightweight model architecture for semantic segmentation.
- Optimize training processes and implement advanced techniques for performance improvement.
- Train the model using high-performance resources.
- Provide detailed documentation and actionable insights for further refinement.
Deliverables:
- A trained model achieving the target mIoU with a novel architecture.
- Updated, well-documented code with clear comments.
- A comprehensive report on the approach and training process.
Your expertise and resources will be pivotal in achieving this milestone.
Requirements:
- Experience in hyperparameter tuning, data augmentation, and fine-tuning.
- Access to a GPU or high-performance computing resources.
Responsibilities:
- Design a novel, lightweight model architecture for semantic segmentation.
- Optimize training processes and implement advanced techniques for performance improvement.
- Train the model using high-performance resources.
- Provide detailed documentation and actionable insights for further refinement.
Deliverables:
- A trained model achieving the target mIoU with a novel architecture.
- Updated, well-documented code with clear comments.
- A comprehensive report on the approach and training process.
Your expertise and resources will be pivotal in achieving this milestone.