Computer Vision

By Rashmi Patel

Master Computer Vision from First Principles to Production Systems

Whether you're a student, AI engineer, software developer, researcher, or interview candidate, this comprehensive guide takes you from the fundamentals of computer vision to building production-ready AI applications. The book is designed as both a practical reference and a graduate-level learning resource, covering the mathematics, algorithms, deep learning architectures, deployment strategies, and real-world implementation of modern computer vision systems.

Inside this book, you'll learn:

Image fundamentals, pixels, color spaces, and digital image representationClassical computer vision techniques including filtering, edge detection, feature extraction, and segmentationConvolutional Neural Networks (CNNs) from fundamentals to implementationModern object detection algorithms including YOLOSemantic and instance segmentation using U-Net and Mask R-CNNTransfer Learning and pretrained vision modelsVision Transformers (ViTs)GANs, Diffusion Models, and Generative Computer Vision3D Computer Vision, Camera Geometry, and Depth EstimationVideo Analytics, Object Tracking, and Action RecognitionFoundation Vision Models including CLIP, SAM, Grounding DINO, Florence-2, and DINOv2Vision-Language Models and multimodal AIProduction deployment, optimization, monitoring, and MLOps for Computer VisionThree complete end-to-end capstone projects with production workflowsInterview questions and answers in every chapterPractical Python implementations using OpenCV, PyTorch, Ultralytics YOLO, and Hugging Face libraries

Unlike books that focus only on theory or only on code, this guide combines intuitive explanations, mathematical foundations, architecture diagrams, production engineering practices, and hands-on implementations into one complete reference.

Whether you're preparing for technical interviews, building production AI systems, pursuing graduate studies, or expanding your professional skills, this book provides a practical roadmap from pixels to intelligent vision systems.

Perfect for:

AI & Machine Learning EngineersComputer Vision EngineersData ScientistsSoftware DevelopersGraduate & Undergraduate StudentsResearchersTechnical Interview PreparationProfessionals building production AI applications

• Format: Paperback
• Language: English
• ISBN: B0HCW27KFQ
• ISBN13: 9798189866494
• Release Date: July 2026
• Publisher: Independently Published
• Length: 160 Pages
• Weight: 0.49 lbs.
• Dimensions: 0.3" x 6.0" x 9.0"