Deep Learning in Action: Image and Video Processing for Practical Use

Grab attention with a clear, practical guide to modern computer vision: Deep Learning in Action: Image and Video Processing for Practical Use by Abdussalam Elhanashi and Sergio Saponara is a hands-on manual designed for engineers, researchers, and professionals who want to apply deep learning to real-world image and video challenges.

Explore focused, industry-ready techniques that bring theory into practice. The authors walk you through convolutional neural networks, object detection, semantic segmentation, video analytics, and optimization strategies, explaining when to choose TensorFlow, PyTorch, or lightweight architectures for edge deployment. Case studies span autonomous driving, smart cities, medical imaging, and industrial inspection—proven examples that resonate across Europe, North America, Asia, and beyond.

Build confidence with clear code snippets, performance-tuning tips, and deployment workflows that address noisy data, limited compute, and real-time inference. This book balances foundational math with pragmatic guidance, making complex topics accessible without sacrificing rigor.

Whether you’re upskilling for a career in computer vision or leading a cross-functional team, this title helps you deliver measurable results—faster prototyping, more reliable models, and smoother production rollout. Its global perspective and practical emphasis make it a valuable resource for startups, established firms, and academic programs alike.

Ready to turn images and video into actionable intelligence? Add Deep Learning in Action: Image and Video Processing for Practical Use to your library today and start building production-grade computer vision solutions.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.