Project Overview
Key features include:
- Deep Learning Damage Classification Model: Built with Python and YOLOv8, targeting four categories of coastal damage for better disaster response.
- Improved Detection Accuracy: Achieved a 40% improvement in damage detection through advanced image processing and model evaluation techniques.
- Team Collaboration: Dedicated 30 hours with a team of three, working closely on model development and evaluation.
Tools Used
Python
YOLOv8
matplotlib
Computer Vision
LabelMe
Git