Computer Vision

Computer vision is revolutionizing industries, enabling machines to interpret and understand images and videos like humans. From facial recognition and self-driving cars to healthcare diagnostics and augmented reality, AI-powered vision systems are shaping the future. But how do these systems work? How can you build your own?

Computer Vision: Teaching AI to See the World is the ninth book in the highly acclaimed AI from Scratch series. Designed for beginners and experienced developers alike, this book provides a step-by-step guide to mastering computer vision, combining fundamental concepts with hands-on implementation using Python, OpenCV, TensorFlow, and PyTorch.

What You'll Learn:

• Foundations of Computer Vision - Understand image processing, pixel manipulation, and edge detection.
• Feature Detection & Classical Techniques - Learn SIFT, HOG, and Viola-Jones for object recognition.
• Deep Learning for Vision - Build CNNs, YOLO, and U-Net for object detection and image segmentation.
• Generative AI & Vision Transformers - Explore GANs for image synthesis and ViTs for state-of-the-art AI vision.
• Real-World Applications - Implement AI-powered security, facial recognition, and medical imaging solutions.
• Ethical AI & Future Trends - Understand AI bias, privacy challenges, and the future of computer vision.

• AI Enthusiasts & Beginners - No prior experience needed! Learn computer vision step by step.
• Developers & Data Scientists - Implement vision models using open-source AI tools.
• Students & Educators - A structured and practical guide to teaching and learning AI vision.
• Researchers & Engineers - Stay updated with cutting-edge deep learning and vision models.