Welcome to the Computer Vision repository! This repository is divided into two main sections: Concepts, which provides theoretical foundations, and Practical Projects, where real-world applications of computer vision techniques are showcased.
This section contains foundational resources for understanding key concepts in Computer Vision. Topics include image processing, convolutional neural networks, and object detection techniques. Click the link below to explore:
- Concepts
Access theoretical resources, including overviews on CNNs, image segmentation, feature extraction, and more.
Here is a list of practical projects that demonstrate the applications of Computer Vision across various domains. Each project includes code, documentation, and examples for hands-on learning.
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Land Use and Land Cover Classification
Classify land use and cover using the EUROSAT dataset with high accuracy -
CV Football Analysis System
This project leverages AI/ML techniques, including YOLO, OpenCV, and Python, to analyze football matches, track player movements, and provide insights through computer vision.
This Computer Vision repository provides both a theoretical base and practical projects for learning and implementing computer vision techniques. Whether you're a beginner or advanced user, this repository offers resources and projects for a range of expertise levels.
For more of my projects, check out my GitHub profile.