Assignment 33

Autonomous Systems and Machine​ assignment

Assignment Briefing: Autonomous Systems and Machine Learning

The Autonomous Systems and Machine Learning assignment involves developing a deep learning model using YOLOv8 in Google Colab to accurately detect objects in images, focusing on applications in computer vision for surveillance, autonomous vehicles, and image understanding. The project showcases proficiency in data preparation, model training, and performance evaluation using mean Average Precision (mAP) metrics.

 

Project Highlights:

• Data Preparation: Processed a dataset of 968 images from two aquariums in the United States, including image augmentation and dataset splitting into training, validation, and test sets.
• Model Development: Implemented a YOLOv8 model with custom training, using 40 epochs to optimize model accuracy and performance stability.
• Evaluation and Validation: Achieved a mAP50 of 79.8%, demonstrating the model’s strong performance in detecting marine animals like fish, jellyfish, penguins, sharks, puffins, stingrays, and starfish.
• Challenges and Improvements: Addressed computational limitations, optimized hyperparameters, and proposed future enhancements such as dataset variability and model scalability.

This assignment demonstrates advanced skills in deep learning, autonomous systems, and the ability to build robust object detection models for real-world applications in autonomous systems and machine learning environments.

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