Deep Learning Technologies
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The Development of Deep Learning Technologies
Author: China Info & Comm Tech Grp Corp
language: en
Publisher: Springer Nature
Release Date: 2020-07-13
This book is a part of the Blue Book series “Research on the Development of Electronic Information Engineering Technology in China,” which explores the cutting edge of deep learning studies. A subfield of machine learning, deep learning differs from conventional machine learning methods in its ability to learn multiple levels of representation and abstraction by using several layers of nonlinear modules for feature extraction and transformation. The extensive use and huge success of deep learning in speech, CV, and NLP have led to significant advances toward the full materialization of AI. Focusing on the development of deep learning technologies, this book also discusses global trends, the status of deep learning development in China and the future of deep learning.
Deep Learning Technologies
Author: Dr.VV.Sunil Kumar
language: en
Publisher: Leilani Katie Publication
Release Date: 2025-01-22
Dr.VV.Sunil Kumar, Professor, Department of Computer Science and Engineering, PBR Visvodaya Institute of Technology and Science, Kavali, SPSR Nellore, Andhra Pradesh, India. Dr.G.Vijay Kumar, Professor, Department of Computer Science and Engineering, PBR Visvodaya Institute of Technology and Science, Kavali, SPSR Nellore, Andhra Pradesh, India.
Deep Learning Technologies for the Sustainable Development Goals
This book provides insights into deep learning techniques that impact the implementation strategies toward achieving the Sustainable Development Goals (SDGs) laid down by the United Nations for its 2030 agenda, elaborating on the promises, limits, and the new challenges. It also covers the challenges, hurdles, and opportunities in various applications of deep learning for the SDGs. A comprehensive survey on the major applications and research, based on deep learning techniques focused on SDGs through speech and image processing, IoT, security, AR-VR, formal methods, and blockchain, is a feature of this book. In particular, there is a need to extend research into deep learning and its broader application to many sectors and to assess its impact on achieving the SDGs. The chapters in this book help in finding the use of deep learning across all sections of SDGs. The rapid development of deep learning needs to be supported by the organizational insight and oversight necessary for AI-based technologies in general; hence, this book presents and discusses the implications of how deep learning enables the delivery agenda for sustainable development.