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Computer Vision

Computer Vision

Dive into the realm of computer vision, a pioneering domain of AI that enables machines to interpret visual data from images and videos. Through computer vision, explore groundbreaking applications such as facial recognition, autonomous vehicles, medical imaging, and quality control in manufacturing.

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  • Kaggle's Computer Vision (opens in a new tab): Offers a beginner-friendly introduction to the field, covering image processing topics. They also provide deep learning and computer vision projects, enhancing practical experience. Kaggle's robust tools and resources, along with collaborative competitions, help you grow in computer vision. Ideal for beginners and those expanding their skills.

  • OpenCV (opens in a new tab): Provide a robust resource for computer vision and image processing. Topics include OpenCV installation, core functionality, image manipulation, high-level GUI, and diverse modules like ML, object detection, and GPU-accelerated computer vision. These tutorials accommodate Python, C++, and JavaScript developers, available in different versions, empowering learners to explore a wide range of computer vision techniques


  • Programming Computer Vision with Python (opens in a new tab): By Jan Erik Solem, offers a hands-on approach to computer vision, teaching techniques like object recognition and 3D reconstruction, includes code samples, exercises, and covers diverse topics. The book is ideal for those with basic programming skills and integrates OpenCV through a Python interface.

  • Computer Vision: Algorithms and Applications (opens in a new tab): By Richard Szeliski is a comprehensive book covering various computer vision topics and real-world applications, including medical imaging, consumer-level tasks, providing complete code samples, explanations, and exercises. Based on Szeliski's courses at top universities, it serves as a valuable resource for computer science and engineering students.

  • Learning OpenCV 3: Computer Vision in C++ (opens in a new tab): By Adrian Kaehler & Gary Bradski is a practical guide to computer vision using OpenCV. It covers essential tools, tracking, and qualitative analysis, offering insights into 3D reconstruction, provides hands-on learning with code examples and exercises, relevant to diverse fields like automation and IoT.