AI/ML Completed
Marine Object Detection
Deep learning model for detecting and classifying marine life and underwater objects using computer vision.
Timeline
Sep 2024 - Feb 2025
Category
AI/ML
Status
completed
Technologies Used
PyTorch YOLO Python OpenCV
Key Highlights
- 95% detection accuracy
- Real-time inference
- Custom dataset of 10,000+ images
Overview
A custom-trained YOLO model for detecting and classifying marine objects in underwater imagery, designed to work with ROV camera feeds in real-time.
Architecture
The system uses a fine-tuned YOLOv8 model trained on a curated dataset of underwater images, with classes including fish species, coral types, marine debris, and infrastructure components.
Results
The model achieves 95% [email protected] on the test set using real-time inference at 30+ FPS on an NVIDIA Jetson platform.