Swimming Pool Detection
Computer vision coursework project focused on transfer learning and aerial object detection.
Built a YOLOv11 object detection model to identify swimming pools from aerial images. Achieved 95.5% mAP after 30 epochs using transfer learning on a custom-labeled dataset with GroundingDINO + Roboflow.
Key Outcomes
Context
Problem and Context
Built a YOLOv11 object detection model to identify swimming pools from aerial images. Achieved 95.5% mAP after 30 epochs using transfer learning on a custom-labeled dataset with GroundingDINO + Roboflow.
Approach
Approach and Architecture
YOLOv11 aerial detection of pools using transfer learning and custom labels.
Implementation
Implementation Details
Results
Results and Tradeoffs
This project is presented as a concise technical overview rather than a full-length narrative case study.
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