Semantic Segmentation Data Preparation for Real-Time Scene Segmentation
OtherImageSegmentation
I trained and evaluated a real-time semantic segmentation pipeline using datasets containing labeled images. My work involved using pre-annotated segmentation masks to improve model performance for drivable-area detection. The project required working with pixel-wise segmented ground truth to fine-tune deep learning architectures.
• Utilized Cityscapes and BDD100K datasets with thousands of annotated images.
• Focused on drivable-area detection, optimizing accuracy under realistic road conditions.
• Improved segmentation performance by leveraging model hyperparameter tuning and evaluation metrics.
• Ensured all data labeling quality met the threshold for reliable on-vehicle deployment.
I trained and evaluated a real-time semantic segmentation pipeline using datasets containing labeled images. My work involved using pre-annotated segmentation masks to improve model performance for drivable-area detection. The project required working with pixel-wise segmented ground truth to fine-tune deep learning architectures. • Utilized Cityscapes and BDD100K datasets with thousands of annotated images. • Focused on drivable-area detection, optimizing accuracy under realistic road conditions. • Improved segmentation performance by leveraging model hyperparameter tuning and evaluation metrics. • Ensured all data labeling quality met the threshold for reliable on-vehicle deployment.
2025 - 2025