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Author: Biao Luo
Publisher: Springer Nature
ISBN: 9819980828
Category : Computers
Languages : en
Pages : 607
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Book Description
The six-volume set LNCS 14447 until 14452 constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 652 papers presented in the proceedings set were carefully reviewed and selected from 1274 submissions. They focus on theory and algorithms, cognitive neurosciences; human centred computing; applications in neuroscience, neural networks, deep learning, and related fields.
Author: Biao Luo
Publisher: Springer Nature
ISBN: 9819980828
Category : Computers
Languages : en
Pages : 607
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Book Description
The six-volume set LNCS 14447 until 14452 constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 652 papers presented in the proceedings set were carefully reviewed and selected from 1274 submissions. They focus on theory and algorithms, cognitive neurosciences; human centred computing; applications in neuroscience, neural networks, deep learning, and related fields.
Author: Michael Wand
Publisher: Springer Nature
ISBN: 3031723449
Category :
Languages : en
Pages : 462
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Book Description
Author: IEEE Staff
Publisher:
ISBN: 9781665445979
Category :
Languages : en
Pages :
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Book Description
JCNN is the premier international conference on neural networks theory, analysis, and a wide range of applications IJCNN 2021 is a truly interdisciplinary event with a broad range of contributions on recent advances in neural networks, including neuroscience and cognitive science, computational intelligence and machine learning, hybrid techniques, nonlinear dynamics and chaos, various soft computing technologies, bioinformatics and biomedicine, and engineering applications
Author: Ullrich Köthe
Publisher: Springer Nature
ISBN: 3031546059
Category :
Languages : en
Pages : 648
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Book Description
Author: Shyam Singh Rajput
Publisher: Academic Press
ISBN: 0323985785
Category : Computers
Languages : en
Pages : 380
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Book Description
Digital Image Enhancement and Reconstruction: Techniques and Applications explores different concepts and techniques used for the enhancement as well as reconstruction of low-quality images. Most real-life applications require good quality images to gain maximum performance, however, the quality of the images captured in real-world scenarios is often very unsatisfactory. Most commonly, images are noisy, blurry, hazy, tiny, and hence need to pass through image enhancement and/or reconstruction algorithms before they can be processed by image analysis applications. This book comprehensively explores application-specific enhancement and reconstruction techniques including satellite image enhancement, face hallucination, low-resolution face recognition, medical image enhancement and reconstruction, reconstruction of underwater images, text image enhancement, biometrics, etc. Chapters will present a detailed discussion of the challenges faced in handling each particular kind of image, analysis of the best available solutions, and an exploration of applications and future directions. The book provides readers with a deep dive into denoising, dehazing, super-resolution, and use of soft computing across a range of engineering applications. - Presents comprehensive coverage of digital image enhancement and reconstruction techniques - Explores applications across range of fields, including intelligent surveillance systems, human-computer interaction, healthcare, agriculture, biometrics, modelling - Explores different challenges and issues related to the implementation of various techniques for different types of images, including denoising, dehazing, super-resolution, and use of soft computing
Author: Ansgar Steland
Publisher: Springer Nature
ISBN: 3031071557
Category : Mathematics
Languages : en
Pages : 378
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Book Description
This book discusses the interplay between statistics, data science, machine learning and artificial intelligence, with a focus on environmental science, the natural sciences, and technology. It covers the state of the art from both a theoretical and a practical viewpoint and describes how to successfully apply machine learning methods, demonstrating the benefits of statistics for modeling and analyzing high-dimensional and big data. The book’s expert contributions include theoretical studies of machine learning methods, expositions of general methodologies for sound statistical analyses of data as well as novel approaches to modeling and analyzing data for specific problems and areas. In terms of applications, the contributions deal with data as arising in industrial quality control, autonomous driving, transportation and traffic, chip manufacturing, photovoltaics, football, transmission of infectious diseases, Covid-19 and public health. The book will appeal to statisticians and data scientists, as well as engineers and computer scientists working in related fields or applications.
Author: Alberto Marchisio
Publisher: CRC Press
ISBN: 1040165036
Category : Computers
Languages : en
Pages : 361
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Book Description
Machine Learning (ML) algorithms have shown a high level of accuracy, and applications are widely used in many systems and platforms. However, developing efficient ML-based systems requires addressing three problems: energy-efficiency, robustness, and techniques that typically focus on optimizing for a single objective/have a limited set of goals. This book tackles these challenges by exploiting the unique features of advanced ML models and investigates cross-layer concepts and techniques to engage both hardware and software-level methods to build robust and energy-efficient architectures for these advanced ML networks. More specifically, this book improves the energy efficiency of complex models like CapsNets, through a specialized flow of hardware-level designs and software-level optimizations exploiting the application-driven knowledge of these systems and the error tolerance through approximations and quantization. This book also improves the robustness of ML models, in particular for SNNs executed on neuromorphic hardware, due to their inherent cost-effective features. This book integrates multiple optimization objectives into specialized frameworks for jointly optimizing the robustness and energy efficiency of these systems. This is an important resource for students and researchers of computer and electrical engineering who are interested in developing energy efficient and robust ML.
Author: Kumari, Aparna
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 370
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Book Description
In an increasingly data-centric world, scholars and practitioners grapple with the complexities of harnessing data analytics effectively across various industries. The challenge lies in navigating the rapid evolution of methodologies, identifying emerging trends, and understanding the nuanced applications of data analytics in real-world scenarios. This gap between theory and practice inhibits academic progress. It hampers industry innovation, leaving stakeholders needing help to leverage data to its full potential. Recent Trends and Future Direction for Data Analytics presents a compelling solution. By delving into real-world case studies spanning supply chain management, marketing, healthcare, and finance, this book bridges the gap between theory and practice, offering invaluable insights into the practical applications of data analytics. A systematic exploration of fundamental concepts, advanced techniques, and specialized topics equips scholars, researchers, and industry professionals with the knowledge and tools needed to navigate the complexities of data analytics with confidence.
Author: Pawan Whig
Publisher: CRC Press
ISBN: 1040228771
Category : Computers
Languages : en
Pages : 287
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Book Description
Artificial Intelligence and Machine Learning for Sustainable Development is a comprehensive exploration of how artificial intelligence (AI) and machine learning (ML) technologies are revolutionizing the field of sustainable development. The book examines cutting-edge innovations, practical applications, and potential challenges in harnessing AI and ML to address global sustainability issues. It offers insights into how these technologies can optimize resource management, improve environmental monitoring, enhance decision-making processes, and promote equitable, eco-friendly solutions. This book would be of special interest to researchers, policymakers, and practitioners seeking to leverage cutting-edge technology for a more sustainable future.
Author: Witold Pedrycz
Publisher: Springer Nature
ISBN: 3030952398
Category : Computers
Languages : en
Pages : 346
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Book Description
This book provides timely studies on multi-view facets of data analytics by covering recent trends in processing and reasoning about data originating from an array of local sources. A multi-view nature of data analytics is encountered when working with a variety of real-world scenarios including clustering, consensus building in decision processes, computer vision, knowledge representation, big data, data streaming, among others. The chapters demonstrate recent pursuits in the methodology, theory, advanced algorithms, and applications of multi-view data analytics and bring new perspectives of data interpretation. The timely book will appeal to a broad readership including both researchers and practitioners interested in gaining exposure to the rapidly growing trend of multi-view data analytics and intelligent systems.
