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Author: Lei Chen
Publisher: Springer Nature
ISBN: 9811622337
Category : Computers
Languages : en
Pages : 403
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Book Description
This book systematically introduces readers to the theory of deep learning and explores its practical applications based on the MindSpore AI computing framework. Divided into 14 chapters, the book covers deep learning, deep neural networks (DNNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), unsupervised learning, deep reinforcement learning, automated machine learning, device-cloud collaboration, deep learning visualization, and data preparation for deep learning. To help clarify the complex topics discussed, this book includes numerous examples and links to online resources.
Author: Lei Chen
Publisher: Springer Nature
ISBN: 9811622337
Category : Computers
Languages : en
Pages : 403
Get Book Here
Book Description
This book systematically introduces readers to the theory of deep learning and explores its practical applications based on the MindSpore AI computing framework. Divided into 14 chapters, the book covers deep learning, deep neural networks (DNNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), unsupervised learning, deep reinforcement learning, automated machine learning, device-cloud collaboration, deep learning visualization, and data preparation for deep learning. To help clarify the complex topics discussed, this book includes numerous examples and links to online resources.
Author: Aboul Ella Hassanien
Publisher: Springer Nature
ISBN: 3031039181
Category : Technology & Engineering
Languages : en
Pages : 708
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Book Description
This book constitutes the refereed proceedings of the 8th International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2022, held in Cairo, Egypt, during May 5-7, 2022. The 8th edition of AMLTA will be organized by the Scientific Research Group in Egypt (SRGE), Egypt, collaborating with Port Said University, Egypt, and VSB-Technical University of Ostrava, Czech Republic. AMLTA series aims to become the premier international conference for an in-depth discussion on the most up-to-date and innovative ideas, research projects, and practices in the field of machine learning technologies and their applications. The book covers current research on advanced machine learning technology, including deep learning technology, sentiment analysis, cyber-physical system, IoT, and smart cities informatics and AI against COVID-19, data mining, power and control systems, business intelligence, social media, digital transformation, and smart systems.
Author: M. Shamim Hossain
Publisher: Springer Nature
ISBN: 3031380363
Category :
Languages : en
Pages : 240
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Book Description
Author: Pramanik, Sabyasachi
Publisher: IGI Global
ISBN: 1668464101
Category : Mathematics
Languages : en
Pages : 499
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Book Description
A smart city utilizes ICT technologies to improve the working effectiveness, share various data with the citizens, and enhance political assistance and societal wellbeing. The fundamental needs of a smart and sustainable city are utilizing smart technology for enhancing municipal activities, expanding monetary development, and improving citizens’ standards of living. The Handbook of Research on Data-Driven Mathematical Modeling in Smart Cities discusses new mathematical models in smart and sustainable cities using big data, visualization tools in mathematical modeling, machine learning-based mathematical modeling, and more. It further delves into privacy and ethics in data analysis. Covering topics such as deep learning, optimization-based data science, and smart city automation, this premier reference source is an excellent resource for mathematicians, statisticians, computer scientists, civil engineers, government officials, students and educators of higher education, librarians, researchers, and academicians.
Author: Romil Rawat
Publisher: John Wiley & Sons
ISBN: 1394152256
Category : Technology & Engineering
Languages : en
Pages : 356
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Book Description
AUTONOMOUS VEHICLES The companion to Autonomous Vehicles Volume 1: Using Machine Intelligence, this second volume in the two-volume set covers intelligent techniques utilized for designing, controlling, and managing vehicular systems based on advanced algorithms of computing like machine learning, artificial intelligence, data analytics, and Internet of Things (IoT) with prediction approaches to avoid accidental damages, security threats, and theft. Besides communicating with other vehicles, self-driving cars connected to a 5G network will also be able to communicate with different infrastructure elements that make up our roads and other transportation and communication systems. Similarly, an unmanned aerial vehicle (UAV), an aircraft without any human pilot, crew, or passengers on board, can operate under remote control by a human operator, as a remotely-piloted aircraft (RPA), or with various degrees of autonomy. These include autopilot assistance and fully autonomous aircraft that have no provision for human intervention. Transportation is a necessary, but often painful process. With fully autonomous driving, passengers will be freed to accomplish their own goals, turning the dead hours of driving into fruitful hours of learning, working, engaging, and relaxing. Similarly, UAVs can perform functions that human-operated aircraft cannot, whether because of the environment or high-risk situations. The purpose of the book is to present the needs, designs, and applications of autonomous vehicles. The topics covered range from mechanical engineering to computer science engineering, both areas playing vital roles in programming, managing, generating alerts, and GPS position, artificial intelligence-based prediction of path and events, as well as other high-tech tools, are covered in this book, as well. Whether for the student, veteran engineer, or another industry professional, this book, and its companion volume, are must-haves for any library.
Author: Honghao Gao
Publisher: Springer Nature
ISBN: 3031243862
Category : Computers
Languages : en
Pages : 544
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Book Description
The two-volume set LNICST 460 and 461 constitutes the proceedings of the 18th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2022, held in Hangzhou, China, in October 2022. The 57 full papers presented in the proceedings were carefully reviewed and selected from 171 submissions. The papers are organized in the following topical sections: Recommendation System; Federated Learning and application; Edge Computing and Collaborative working; Blockchain applications; Security and Privacy Protection; Deep Learning and application; Collaborative working; Images processing and recognition.
Author: Wenjie Zhang
Publisher: Springer Nature
ISBN: 9819772443
Category :
Languages : en
Pages : 531
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Book Description
Author: Fei Liu
Publisher: Springer Nature
ISBN: 3031446968
Category : Computers
Languages : en
Pages : 885
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Book Description
This three-volume set constitutes the refereed proceedings of the 12th National CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2023, held in Foshan, China, during October 12–15, 2023. The ____ regular papers included in these proceedings were carefully reviewed and selected from 478 submissions. They were organized in topical sections as follows: dialogue systems; fundamentals of NLP; information extraction and knowledge graph; machine learning for NLP; machine translation and multilinguality; multimodality and explainability; NLP applications and text mining; question answering; large language models; summarization and generation; student workshop; and evaluation workshop.
Author: Biao Luo
Publisher: Springer Nature
ISBN: 9819981263
Category : Neural computers
Languages : en
Pages : 603
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Book Description
The nine-volume set constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 1274 papers presented in the proceedings set were carefully reviewed and selected from 652 submissions. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.
Author: Chuan Shi
Publisher: Springer Nature
ISBN: 3031161742
Category : Mathematics
Languages : en
Pages : 207
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Book Description
This book provides a comprehensive introduction to the foundations and frontiers of graph neural networks. In addition, the book introduces the basic concepts and definitions in graph representation learning and discusses the development of advanced graph representation learning methods with a focus on graph neural networks. The book providers researchers and practitioners with an understanding of the fundamental issues as well as a launch point for discussing the latest trends in the science. The authors emphasize several frontier aspects of graph neural networks and utilize graph data to describe pairwise relations for real-world data from many different domains, including social science, chemistry, and biology. Several frontiers of graph neural networks are introduced, which enable readers to acquire the needed techniques of advances in graph neural networks via theoretical models and real-world applications.
