Application Of Artificial Intelligence And Machine Learning To Accelerators

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Hardware Accelerator Systems for Artificial Intelligence and Machine Learning

Author : Shiho Kim
Publisher : Elsevier
ISBN 13 : 0128231238
Total Pages : 414 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Hardware Accelerator Systems for Artificial Intelligence and Machine Learning by : Shiho Kim

Download or read book Hardware Accelerator Systems for Artificial Intelligence and Machine Learning written by Shiho Kim and published by Elsevier. This book was released on 2021-04-07 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Volume 122 delves into arti?cial Intelligence and the growth it has seen with the advent of Deep Neural Networks (DNNs) and Machine Learning. Updates in this release include chapters on Hardware accelerator systems for artificial intelligence and machine learning, Introduction to Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Deep Learning with GPUs, Edge Computing Optimization of Deep Learning Models for Specialized Tensor Processing Architectures, Architecture of NPU for DNN, Hardware Architecture for Convolutional Neural Network for Image Processing, FPGA based Neural Network Accelerators, and much more. Updates on new information on the architecture of GPU, NPU and DNN Discusses In-memory computing, Machine intelligence and Quantum computing Includes sections on Hardware Accelerator Systems to improve processing efficiency and performance

Application of Artificial Intelligence and Machine Learning to Accelerators

Author : Robert Garnett
Publisher : Frontiers Media SA
ISBN 13 : 283253774X
Total Pages : 113 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis Application of Artificial Intelligence and Machine Learning to Accelerators by : Robert Garnett

Download or read book Application of Artificial Intelligence and Machine Learning to Accelerators written by Robert Garnett and published by Frontiers Media SA. This book was released on 2023-10-31 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) and Machine learning (ML) promise significant enhancements for particle accelerator operations, including applications in diagnostics, controls, and modeling. Challenges still exist in experimentally verifying AI/ML methods before deployment at user facilities. The ability to quickly generalize and adapt these methods to new operating configurations at the same facility or between facilities also remains a challenge and requires combining model-independent adaptive feedback with traditional ML tools. These methods also apply to the detection, classification, and prevention of operational anomalies that can cause accelerator damage or excessive beam loss in the case of abnormal operations. Opportunity exists in broadening AI/ML methods for early detection of a broad range of accelerator component or subsystem failures.

Efficient Processing of Deep Neural Networks

Author : Vivienne Sze
Publisher : Springer Nature
ISBN 13 : 3031017668
Total Pages : 254 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Efficient Processing of Deep Neural Networks by : Vivienne Sze

Download or read book Efficient Processing of Deep Neural Networks written by Vivienne Sze and published by Springer Nature. This book was released on 2022-05-31 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs). DNNs are currently widely used for many artificial intelligence (AI) applications, including computer vision, speech recognition, and robotics. While DNNs deliver state-of-the-art accuracy on many AI tasks, it comes at the cost of high computational complexity. Therefore, techniques that enable efficient processing of deep neural networks to improve key metrics—such as energy-efficiency, throughput, and latency—without sacrificing accuracy or increasing hardware costs are critical to enabling the wide deployment of DNNs in AI systems. The book includes background on DNN processing; a description and taxonomy of hardware architectural approaches for designing DNN accelerators; key metrics for evaluating and comparing different designs; features of DNN processing that are amenable to hardware/algorithm co-design to improve energy efficiency and throughput; and opportunities for applying new technologies. Readers will find a structured introduction to the field as well as formalization and organization of key concepts from contemporary work that provide insights that may spark new ideas.

Machine Learning and AI for Healthcare

Author : Arjun Panesar
Publisher : Apress
ISBN 13 : 1484237994
Total Pages : 390 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Machine Learning and AI for Healthcare by : Arjun Panesar

Download or read book Machine Learning and AI for Healthcare written by Arjun Panesar and published by Apress. This book was released on 2019-02-04 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the theory and practical applications of artificial intelligence (AI) and machine learning in healthcare. This book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare and big data challenges. You’ll discover the ethical implications of healthcare data analytics and the future of AI in population and patient health optimization. You’ll also create a machine learning model, evaluate performance and operationalize its outcomes within your organization. Machine Learning and AI for Healthcare provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of AI applications. These are illustrated through leading case studies, including how chronic disease is being redefined through patient-led data learning and the Internet of Things. What You'll LearnGain a deeper understanding of key machine learning algorithms and their use and implementation within wider healthcare Implement machine learning systems, such as speech recognition and enhanced deep learning/AI Select learning methods/algorithms and tuning for use in healthcare Recognize and prepare for the future of artificial intelligence in healthcare through best practices, feedback loops and intelligent agentsWho This Book Is For Health care professionals interested in how machine learning can be used to develop health intelligence – with the aim of improving patient health, population health and facilitating significant care-payer cost savings.

Practical Deep Learning for Cloud, Mobile, and Edge

Author : Anirudh Koul
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492034819
Total Pages : 585 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Practical Deep Learning for Cloud, Mobile, and Edge by : Anirudh Koul

Download or read book Practical Deep Learning for Cloud, Mobile, and Edge written by Anirudh Koul and published by "O'Reilly Media, Inc.". This book was released on 2019-10-14 with total page 585 pages. Available in PDF, EPUB and Kindle. Book excerpt: Whether you’re a software engineer aspiring to enter the world of deep learning, a veteran data scientist, or a hobbyist with a simple dream of making the next viral AI app, you might have wondered where to begin. This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile, browsers, and edge devices using a hands-on approach. Relying on years of industry experience transforming deep learning research into award-winning applications, Anirudh Koul, Siddha Ganju, and Meher Kasam guide you through the process of converting an idea into something that people in the real world can use. Train, tune, and deploy computer vision models with Keras, TensorFlow, Core ML, and TensorFlow Lite Develop AI for a range of devices including Raspberry Pi, Jetson Nano, and Google Coral Explore fun projects, from Silicon Valley’s Not Hotdog app to 40+ industry case studies Simulate an autonomous car in a video game environment and build a miniature version with reinforcement learning Use transfer learning to train models in minutes Discover 50+ practical tips for maximizing model accuracy and speed, debugging, and scaling to millions of users

Hardware Accelerator Systems for Artificial Intelligence and Machine Learning

Author :
Publisher : Academic Press
ISBN 13 : 0128231246
Total Pages : 416 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Hardware Accelerator Systems for Artificial Intelligence and Machine Learning by :

Download or read book Hardware Accelerator Systems for Artificial Intelligence and Machine Learning written by and published by Academic Press. This book was released on 2021-03-28 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Volume 122 delves into arti?cial Intelligence and the growth it has seen with the advent of Deep Neural Networks (DNNs) and Machine Learning. Updates in this release include chapters on Hardware accelerator systems for artificial intelligence and machine learning, Introduction to Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Deep Learning with GPUs, Edge Computing Optimization of Deep Learning Models for Specialized Tensor Processing Architectures, Architecture of NPU for DNN, Hardware Architecture for Convolutional Neural Network for Image Processing, FPGA based Neural Network Accelerators, and much more. - Updates on new information on the architecture of GPU, NPU and DNN - Discusses In-memory computing, Machine intelligence and Quantum computing - Includes sections on Hardware Accelerator Systems to improve processing efficiency and performance

Artificial Intelligence and Hardware Accelerators

Author : Ashutosh Mishra
Publisher : Springer Nature
ISBN 13 : 3031221702
Total Pages : 358 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis Artificial Intelligence and Hardware Accelerators by : Ashutosh Mishra

Download or read book Artificial Intelligence and Hardware Accelerators written by Ashutosh Mishra and published by Springer Nature. This book was released on 2023-03-15 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores new methods, architectures, tools, and algorithms for Artificial Intelligence Hardware Accelerators. The authors have structured the material to simplify readers’ journey toward understanding the aspects of designing hardware accelerators, complex AI algorithms, and their computational requirements, along with the multifaceted applications. Coverage focuses broadly on the hardware aspects of training, inference, mobile devices, and autonomous vehicles (AVs) based AI accelerators

Using artificial intelligence to assess FAO’s knowledge base on the technology accelerator

Author : Food and Agriculture Organization of the United Nations
Publisher : Food & Agriculture Org.
ISBN 13 : 925137967X
Total Pages : 72 pages
Book Rating : 4.2/5 (513 download)

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Book Synopsis Using artificial intelligence to assess FAO’s knowledge base on the technology accelerator by : Food and Agriculture Organization of the United Nations

Download or read book Using artificial intelligence to assess FAO’s knowledge base on the technology accelerator written by Food and Agriculture Organization of the United Nations and published by Food & Agriculture Org.. This book was released on 2023-09-01 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: Harnessing science, technology and innovation (STI) is key to meeting the aspirations of efficient, inclusive, resilient and sustainable agrifood systems and leveraging emerging opportunities to achieve the Sustainable Development Goals (SDGs). The FAO Strategic Framework 2022–2031 identifies STI as having enormous transformative potential and underlines the potential of emerging technologies. It also recognizes that STI can present substantial risks, such as reinforcing inequality and market concentration, or contributing to the degradation of natural resources. As one of four accelerators identified by the FAO Strategic Framework 2022–2031, technology is expected to “accelerate impact while minimizing trade-offs”. This report examines the technology accelerator trends across publicly available FAO knowledge reports, technical guidance and convening summaries. Leveraging AI-assisted classification of nearly 40 000 documents, this report offers a bird’s-eye perspective of six types of technology – digital technologies, biotechnologies, mechanization, irrigation technologies, renewable energy technologies and food processing technologies – as well as high-level trends for outcomes and social and demographic details about the communities using these technologies.

VLSI and Hardware Implementations using Modern Machine Learning Methods

Author : Sandeep Saini
Publisher : CRC Press
ISBN 13 : 1000523810
Total Pages : 329 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis VLSI and Hardware Implementations using Modern Machine Learning Methods by : Sandeep Saini

Download or read book VLSI and Hardware Implementations using Modern Machine Learning Methods written by Sandeep Saini and published by CRC Press. This book was released on 2021-12-30 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning is a potential solution to resolve bottleneck issues in VLSI via optimizing tasks in the design process. This book aims to provide the latest machine-learning–based methods, algorithms, architectures, and frameworks designed for VLSI design. The focus is on digital, analog, and mixed-signal design techniques, device modeling, physical design, hardware implementation, testability, reconfigurable design, synthesis and verification, and related areas. Chapters include case studies as well as novel research ideas in the given field. Overall, the book provides practical implementations of VLSI design, IC design, and hardware realization using machine learning techniques. Features: Provides the details of state-of-the-art machine learning methods used in VLSI design Discusses hardware implementation and device modeling pertaining to machine learning algorithms Explores machine learning for various VLSI architectures and reconfigurable computing Illustrates the latest techniques for device size and feature optimization Highlights the latest case studies and reviews of the methods used for hardware implementation This book is aimed at researchers, professionals, and graduate students in VLSI, machine learning, electrical and electronic engineering, computer engineering, and hardware systems.

Applied Artificial Intelligence: Where AI Can Be Used In Business

Author : Francesco Corea
Publisher : Springer
ISBN 13 : 331977252X
Total Pages : 47 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Applied Artificial Intelligence: Where AI Can Be Used In Business by : Francesco Corea

Download or read book Applied Artificial Intelligence: Where AI Can Be Used In Business written by Francesco Corea and published by Springer. This book was released on 2018-03-09 with total page 47 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with artificial intelligence (AI) and its several applications. It is not an organic text that should be read from the first page onwards, but rather a collection of articles that can be read at will (or at need). The idea of this work is indeed to provide some food for thoughts on how AI is impacting few verticals (insurance and financial services), affecting horizontal and technical applications (speech recognition and blockchain), and changing organizational structures (introducing new figures or dealing with ethical issues). The structure of the chapter is very similar, so I hope the reader won’t find difficulties in establishing comparisons or understanding the differences between specific problems AI is being used for. The first chapter of the book is indeed showing the potential and the achievements of new AI techniques in the speech recognition domain, touching upon the topics of bots and conversational interfaces. The second and thirds chapter tackle instead verticals that are historically data-intensive but not data-driven, i.e., the financial sector and the insurance one. The following part of the book is the more technical one (and probably the most innovative), because looks at AI and its intersection with another exponential technology, namely the blockchain. Finally, the last chapters are instead more operative, because they concern new figures to be hired regardless of the organization or the sector, and ethical and moral issues related to the creation and implementation of new type of algorithms.

Brain-Inspired Computing

Author : Katrin Amunts
Publisher : Springer Nature
ISBN 13 : 3030824276
Total Pages : 159 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Brain-Inspired Computing by : Katrin Amunts

Download or read book Brain-Inspired Computing written by Katrin Amunts and published by Springer Nature. This book was released on 2021-07-20 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book constitutes revised selected papers from the 4th International Workshop on Brain-Inspired Computing, BrainComp 2019, held in Cetraro, Italy, in July 2019. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book. They deal with research on brain atlasing, multi-scale models and simulation, HPC and data infra-structures for neuroscience as well as artificial and natural neural architectures.

Artificial Intelligence Hardware Design

Author : Albert Chun-Chen Liu
Publisher : John Wiley & Sons
ISBN 13 : 1119810477
Total Pages : 244 pages
Book Rating : 4.1/5 (198 download)

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Book Synopsis Artificial Intelligence Hardware Design by : Albert Chun-Chen Liu

Download or read book Artificial Intelligence Hardware Design written by Albert Chun-Chen Liu and published by John Wiley & Sons. This book was released on 2021-08-23 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: ARTIFICIAL INTELLIGENCE HARDWARE DESIGN Learn foundational and advanced topics in Neural Processing Unit design with real-world examples from leading voices in the field In Artificial Intelligence Hardware Design: Challenges and Solutions, distinguished researchers and authors Drs. Albert Chun Chen Liu and Oscar Ming Kin Law deliver a rigorous and practical treatment of the design applications of specific circuits and systems for accelerating neural network processing. Beginning with a discussion and explanation of neural networks and their developmental history, the book goes on to describe parallel architectures, streaming graphs for massive parallel computation, and convolution optimization. The authors offer readers an illustration of in-memory computation through Georgia Tech’s Neurocube and Stanford’s Tetris accelerator using the Hybrid Memory Cube, as well as near-memory architecture through the embedded eDRAM of the Institute of Computing Technology, the Chinese Academy of Science, and other institutions. Readers will also find a discussion of 3D neural processing techniques to support multiple layer neural networks, as well as information like: A thorough introduction to neural networks and neural network development history, as well as Convolutional Neural Network (CNN) models Explorations of various parallel architectures, including the Intel CPU, Nvidia GPU, Google TPU, and Microsoft NPU, emphasizing hardware and software integration for performance improvement Discussions of streaming graph for massive parallel computation with the Blaize GSP and Graphcore IPU An examination of how to optimize convolution with UCLA Deep Convolutional Neural Network accelerator filter decomposition Perfect for hardware and software engineers and firmware developers, Artificial Intelligence Hardware Design is an indispensable resource for anyone working with Neural Processing Units in either a hardware or software capacity.

Applied Cryptography and Network Security Workshops

Author : Jianying Zhou
Publisher : Springer Nature
ISBN 13 : 3031168151
Total Pages : 630 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Applied Cryptography and Network Security Workshops by : Jianying Zhou

Download or read book Applied Cryptography and Network Security Workshops written by Jianying Zhou and published by Springer Nature. This book was released on 2022-09-23 with total page 630 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the satellite workshops held around the 20th International Conference on Applied Cryptography and Network Security, ACNS 2022, held in Rome, Italy, in June 2022. Due to the Corona pandemic the workshop was held as a virtual event. The 31 papers presented in this volume were carefully reviewed and selected from 52 submissions. They stem from the following workshops: – AIBlock: 4th ACNS Workshop on Application Intelligence and Blockchain Security – AIHWS: 3rd ACNS Workshop on Artificial Intelligence in Hardware Security – AIoTS: 4th ACNS Workshop on Artificial Intelligence and Industrial IoT Security – CIMSS: 2nd ACNS Workshop on Critical Infrastructure and Manufacturing System Security – Cloud S&P: 4th ACNS Workshop on Cloud Security and Privacy – SCI: 3rd ACNS Workshop on Secure Cryptographic Implementation – SecMT: 3rd ACNS Workshop on Security in Mobile Technologies – SiMLA: 4th ACNS Workshop on Security in Machine Learning and its Applications

High Performance Computing for Big Data

Author : Chao Wang
Publisher : CRC Press
ISBN 13 : 1498784003
Total Pages : 287 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis High Performance Computing for Big Data by : Chao Wang

Download or read book High Performance Computing for Big Data written by Chao Wang and published by CRC Press. This book was released on 2017-10-16 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: High-Performance Computing for Big Data: Methodologies and Applications explores emerging high-performance architectures for data-intensive applications, novel efficient analytical strategies to boost data processing, and cutting-edge applications in diverse fields, such as machine learning, life science, neural networks, and neuromorphic engineering. The book is organized into two main sections. The first section covers Big Data architectures, including cloud computing systems, and heterogeneous accelerators. It also covers emerging 3D IC design principles for memory architectures and devices. The second section of the book illustrates emerging and practical applications of Big Data across several domains, including bioinformatics, deep learning, and neuromorphic engineering. Features Covers a wide range of Big Data architectures, including distributed systems like Hadoop/Spark Includes accelerator-based approaches for big data applications such as GPU-based acceleration techniques, and hardware acceleration such as FPGA/CGRA/ASICs Presents emerging memory architectures and devices such as NVM, STT- RAM, 3D IC design principles Describes advanced algorithms for different big data application domains Illustrates novel analytics techniques for Big Data applications, scheduling, mapping, and partitioning methodologies Featuring contributions from leading experts, this book presents state-of-the-art research on the methodologies and applications of high-performance computing for big data applications. About the Editor Dr. Chao Wang is an Associate Professor in the School of Computer Science at the University of Science and Technology of China. He is the Associate Editor of ACM Transactions on Design Automations for Electronics Systems (TODAES), Applied Soft Computing, Microprocessors and Microsystems, IET Computers & Digital Techniques, and International Journal of Electronics. Dr. Chao Wang was the recipient of Youth Innovation Promotion Association, CAS, ACM China Rising Star Honorable Mention (2016), and best IP nomination of DATE 2015. He is now on the CCF Technical Committee on Computer Architecture, CCF Task Force on Formal Methods. He is a Senior Member of IEEE, Senior Member of CCF, and a Senior Member of ACM.

Artificial Intelligence and Machine Learning for Open-world Novelty

Author :
Publisher : Elsevier
ISBN 13 : 0323999298
Total Pages : 378 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Artificial Intelligence and Machine Learning for Open-world Novelty by :

Download or read book Artificial Intelligence and Machine Learning for Open-world Novelty written by and published by Elsevier. This book was released on 2024-02-20 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Computers, Volume presents innovations in computer hardware, software, theory, design and applications, with this updated volume including new chapters on - Contains novel subject matter that is relevant to computer science - Includes the expertise of contributing authors - Presents an easy to comprehend writing style

Intelligent Internet of Things

Author : Farshad Firouzi
Publisher : Springer Nature
ISBN 13 : 3030303675
Total Pages : 647 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Intelligent Internet of Things by : Farshad Firouzi

Download or read book Intelligent Internet of Things written by Farshad Firouzi and published by Springer Nature. This book was released on 2020-01-21 with total page 647 pages. Available in PDF, EPUB and Kindle. Book excerpt: This holistic book is an invaluable reference for addressing various practical challenges in architecting and engineering Intelligent IoT and eHealth solutions for industry practitioners, academic and researchers, as well as for engineers involved in product development. The first part provides a comprehensive guide to fundamentals, applications, challenges, technical and economic benefits, and promises of the Internet of Things using examples of real-world applications. It also addresses all important aspects of designing and engineering cutting-edge IoT solutions using a cross-layer approach from device to fog, and cloud covering standards, protocols, design principles, reference architectures, as well as all the underlying technologies, pillars, and components such as embedded systems, network, cloud computing, data storage, data processing, big data analytics, machine learning, distributed ledger technologies, and security. In addition, it discusses the effects of Intelligent IoT, which are reflected in new business models and digital transformation. The second part provides an insightful guide to the design and deployment of IoT solutions for smart healthcare as one of the most important applications of IoT. Therefore, the second part targets smart healthcare-wearable sensors, body area sensors, advanced pervasive healthcare systems, and big data analytics that are aimed at providing connected health interventions to individuals for healthier lifestyles.

The Use of Artificial Intelligence for Space Applications

Author : Cosimo Ieracitano
Publisher : Springer Nature
ISBN 13 : 3031257553
Total Pages : 444 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis The Use of Artificial Intelligence for Space Applications by : Cosimo Ieracitano

Download or read book The Use of Artificial Intelligence for Space Applications written by Cosimo Ieracitano and published by Springer Nature. This book was released on 2023-06-16 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an ideal and practical resource on the potential impact Artificial Intelligence (AI) can have in space sciences and applications. AI for Space Application presents a hands-on approach to browse in the subject and to learning how to do. AI is not yet fully accepted as a pervasive technology in space applications because they are often mission-critical and the cost of space equipment and modules raises skepticism on any practical use and reliability. However, it is evident that its potential impact on many aspects is dramatic. Starting from either actual or experimental realizations, the book accompanies the reader through such fascinating subjects like space exploration, autonomous navigation and landing, rover control and guidance on rough surfaces, image analysis automation for planet or star classification, and for space debris avoidance without human intervention. This kind of approach may facilitate further investigations on the same or similar subjects, as the future of space explorations is going toward adopting AI. The intended audience of the book are researchers from academia and space industries and practitioners in related start-ups.