Pedro Reviriego – författare

This book provides readers with an overview of the use of digital techniques for cultural heritage preservation. Those include image processing, advanced sensing, geomatics or virtual and augmented reality. The use of newer tools such as generative artificial intelligence for images and 3D or advanced natural language processing systems is also considered. The ultimate goal is to provide readers with a global perspective of the state of the art on the use of digital tools for cultural heritage applications, both for researchers and professionals involved in cultural heritage and for computer scientists and engineers that design and develop technologies that can be used for cultural heritage preservation.

This book provides readers with an overview of the use of digital techniques for cultural heritage preservation. Those include image processing, advanced sensing, geomatics or virtual and augmented reality. The use of newer tools such as generative artificial intelligence for images and 3D or advanced natural language processing systems is also considered. The ultimate goal is to provide readers with a global perspective of the state of the art on the use of digital tools for cultural heritage applications, both for researchers and professionals involved in cultural heritage and for computer scientists and engineers that design and develop technologies that can be used for cultural heritage preservation.

This book addresses the technological contributions and developments of advanced hardware for Machine Learning (ML) computing systems. The authors discuss state-of-the-art progress in this area (and related topics) as well as reporting on their application to diverse fields. This is achieved by chapters covering the entire spectrum of research activities to include design and applications, with a focus on high performance and dependable operation. The entire hardware stack (from circuit, to architecture, up to the system level) is discussed in detail.  The book will cover innovative material as well as tutorials, reviews and surveys of current theoretical/experimental results, design methodologies and applications over a wide spectrum of scope for an enlarged readership, so to include engineers as well as scientists.Discusses a wide range of topics for Machine Learning-based computer systems;Covers design and application for the entire hardware stack, with a focus on high performance and dependability;Includes innovative material, as well as tutorials, reviews and surveys of current theoretical/experimental results.

This book addresses the technological contributions and developments of advanced hardware for Machine Learning (ML) computing systems. The authors discuss state-of-the-art progress in this area (and related topics) as well as reporting on their application to diverse fields. This is achieved by chapters covering the entire spectrum of research activities to include design and applications, with a focus on high performance and dependable operation. The entire hardware stack (from circuit, to architecture, up to the system level) is discussed in detail.  The book will cover innovative material as well as tutorials, reviews and surveys of current theoretical/experimental results, design methodologies and applications over a wide spectrum of scope for an enlarged readership, so to include engineers as well as scientists.Discusses a wide range of topics for Machine Learning-based computer systems;Covers design and application for the entire hardware stack, with a focus on high performance and dependability;Includes innovative material, as well as tutorials, reviews and surveys of current theoretical/experimental results.