Image processing plays a crucial role in various fields, including digital multimedia, automated vision detection and inspection, and pattern recognition. This book provides a comprehensive overview of the mechanisms and techniques involved, with a focus on the application of advanced AI deep learning technologies in image processing.

This book emphasizes the idea of understanding the motivation of the advanced circuits’ design to establish the AI interface and to mitigate the security attacks in a better way for big data. It is for students, researchers, and professionals, faculty members and software developers who wish to carry out further research.

What if theology was never meant to be static? What happens when the act of faith is reimagined across generations, cultures, and now, code? How can diverse theological perspectives work together to build ethical AI?

What if theology was never meant to be static? What happens when the act of faith is reimagined across generations, cultures, and now, code? How can diverse theological perspectives work together to build ethical AI?

AI for Community examines how technology can bridge cultural divides while considering what it means to preserve culture responsibly and human flourishing. It is a vital resource for those seeking to create AI that respects and uplifts communities, and to empower diverse cultures and protect their heritage

AI for Community examines how technology can bridge cultural divides while considering what it means to preserve culture responsibly and human flourishing. It is a vital resource for those seeking to create AI that respects and uplifts communities, and to empower diverse cultures and protect their heritage

This edited book is a multi-disciplinary reference on how domain-aware AI models can outperform generic approaches by addressing sector-specific complexities. It is for academics and researchers in computer science, AI, and data science; industry professionals in transportation, software engineering, finance; and policymakers.

This edited book is a multi-disciplinary reference on how domain-aware AI models can outperform generic approaches by addressing sector-specific complexities. It is for academics and researchers in computer science, AI, and data science; industry professionals in transportation, software engineering, finance; and policymakers.

Moving well beyond simply speeding up computation, this book tackles AI for Finance from a range of perspectives including business, technology, research, and students. Covering aspects like algorithms, big data, and machine learning, this book answers these and many other questions.

AI is reshaping our world. This is the guide you need to stay relevant, work smarter, and future-proof your career.