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

1. Auflage 2025
ISBN: 978-0-443-30079-0
Verlag: Elsevier Science & Techn.
Format: EPUB
Kopierschutz: 6 - ePub Watermark

E-Book, Englisch, 250 Seiten

Artificial intelligence technology has entered an extraordinary phase of fast development and wide application. The techniques developed in traditional AI research areas, such as computer vision and object recognition, have found many innovative applications in an array of real-world settings. The general methodological contributions from AI, such as a variety of recently developed deep learning algorithms, have also been applied to a wide spectrum of fields such as surveillance applications, real-time processing, IoT devices, and health care systems. The state-of-the-art and deep learning models have wider applicability and are highly efficient. Deep Learning in Action: Image and Video Processing for Practical Use provides a comprehensive and accessible resource for both intermediate to advanced readers seeking to harness the power of deep learning in the domains of video and image processing. The book bridges the gap between theoretical concepts and practical implementation by emphasizing lightweight approaches, enabling readers to efficiently apply deep learning techniques to real-world scenarios. It focuses on resource-efficient methods, making it particularly relevant in contexts where computational constraints are a concern. - Provides step-by-step guidance on implementing deep learning techniques, specifically for video and image processing tasks in real-world scenarios - Emphasizes lightweight and efficient approaches to deep learning, ensuring that readers learn techniques that are suited to resource-constrained environments - Covers a wide range of real-world applications, such as object detection, image segmentation, video classification - Offers a comprehensive understanding of how deep learning can be leveraged across various domains - Encourages hands-on experience that can be applied to the concepts to existing projects

Dr. Abdussalam Elhanashi is a researcher at the Università di Pisa, Italy, specializing in advanced applications of deep learning and video imaging processing. He holds an M.Sc. in Electronics and Electrical Engineering from the University of Glasgow in Scotland and an MBA from the University of Nicosia in Cyprus. He earned his Ph.D. in Information Engineering from the Università di Pisa, funded by a prestigious merit-based scholarship from the Islamic Bank Development (IsDB) as Libya's top candidate in 2019-2020. Dr. Elhanashi was a Research Fellow at the University of Strathclyde in 2021, where he applied deep learning models to analyse CT scans and X-ray images for medical diagnostics. In 2022, he was a visiting researcher at Hiroshima University in Japan, focusing on advanced video analysis techniques. With over 16 years of industry experience, he has successfully managed engineering projects, conducted system maintenance, and performed root cause analyses to address technical challenges. He authored the first Arabic-language book on artificial intelligence in Libya and has contributed to numerous peer-reviewed articles in international conferences and journals. He is a developer at the Society for Imaging Informatics in Medicine (SIIM) in USA. His work focuses on real-world AI applications, lightweight model development, video surveillance, IoT-based low-cost embedded systems, designing AI-driven solutions for medical imaging, and efficient coding techniques for imaging and video processing systems.

Autoren/Hrsg.

Elhanashi, Abdussalam

Saponara, Sergio