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Advances In Extreme Learning Machines Elm 2014
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Book Synopsis Proceedings of ELM-2014 Volume 1 by : Jiuwen Cao
Download or read book Proceedings of ELM-2014 Volume 1 written by Jiuwen Cao and published by Springer. This book was released on 2014-12-04 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains some selected papers from the International Conference on Extreme Learning Machine 2014, which was held in Singapore, December 8-10, 2014. This conference brought together the researchers and practitioners of Extreme Learning Machine (ELM) from a variety of fields to promote research and development of “learning without iterative tuning”. The book covers theories, algorithms and applications of ELM. It gives the readers a glance of the most recent advances of ELM.
Book Synopsis Pathological Brain Detection by : Shui-Hua Wang
Download or read book Pathological Brain Detection written by Shui-Hua Wang and published by Springer. This book was released on 2018-07-20 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides detailed practical guidelines on how to develop an efficient pathological brain detection system, reflecting the latest advances in the computer-aided diagnosis of structural magnetic resonance brain images. Matlab codes are provided for most of the functions described. In addition, the book equips readers to easily develop the pathological brain detection system further on their own and apply the technologies to other research fields, such as Alzheimer’s detection, multiple sclerosis detection, etc.
Book Synopsis Proceedings of ELM-2014 Volume 2 by : Jiuwen Cao
Download or read book Proceedings of ELM-2014 Volume 2 written by Jiuwen Cao and published by Springer. This book was released on 2014-12-09 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains some selected papers from the International Conference on Extreme Learning Machine 2014, which was held in Singapore, December 8-10, 2014. This conference brought together the researchers and practitioners of Extreme Learning Machine (ELM) from a variety of fields to promote research and development of “learning without iterative tuning”. The book covers theories, algorithms and applications of ELM. It gives the readers a glance of the most recent advances of ELM.
Book Synopsis Advances in Computational Intelligence by : Ignacio Rojas
Download or read book Advances in Computational Intelligence written by Ignacio Rojas and published by Springer. This book was released on 2015-06-05 with total page 637 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set LNCS 9094 and LNCS 9095 constitutes the thoroughly refereed proceedings of the 13th International Work-Conference on Artificial Neural Networks, IWANN 2015, held in Palma de Mallorca, Spain, in June 2013. The 99 revised full papers presented together with 1 invited talk were carefully reviewed and selected from 195 submissions. The papers are organized in topical sections on brain-computer interfaces: applications and tele-services; multi-robot systems: applications and theory (MRSAT); video and image processing; transfer learning; structures, algorithms and methods in artificial intelligence; interactive and cognitive environments; mathematical and theoretical methods in fuzzy systems; pattern recognition; embedded intelligent systems; expert systems; advances in computational intelligence; and applications of computational intelligence.
Book Synopsis Computational Intelligence by : Diego Andina
Download or read book Computational Intelligence written by Diego Andina and published by Springer Science & Business Media. This book was released on 2007-05-06 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Intelligence is tolerant of imprecise information, partial truth and uncertainty. This book presents a selected collection of contributions on a focused treatment of important elements of CI, centred on its key element: learning. This book presents novel applications and real world applications working in Manufacturing and Engineering, and it sets a basis for understanding Domotic and Production Methods of the XXI Century.
Book Synopsis Proceedings of ELM 2021 by : Kaj-Mikael Björk
Download or read book Proceedings of ELM 2021 written by Kaj-Mikael Björk and published by Springer Nature. This book was released on 2023-01-18 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains papers from the International Conference on Extreme Learning Machine 2021, which was held in virtual on December 15–16, 2021. Extreme learning machines (ELM) aims to enable pervasive learning and pervasive intelligence. As advocated by ELM theories, it is exciting to see the convergence of machine learning and biological learning from the long-term point of view. ELM may be one of the fundamental `learning particles’ filling the gaps between machine learning and biological learning (of which activation functions are even unknown). ELM represents a suite of (machine and biological) learning techniques in which hidden neurons need not be tuned: inherited from their ancestors or randomly generated. ELM learning theories show that effective learning algorithms can be derived based on randomly generated hidden neurons (biological neurons, artificial neurons, wavelets, Fourier series, etc.) as long as they are nonlinear piecewise continuous, independent of training data and application environments. Increasingly, evidence from neuroscience suggests that similar principles apply in biological learning systems. ELM theories and algorithms argue that “random hidden neurons” capture an essential aspect of biological learning mechanisms as well as the intuitive sense that the efficiency of biological learning need not rely on computing power of neurons. ELM theories thus hint at possible reasons why the brain is more intelligent and effective than current computers. This conference provides a forum for academics, researchers, and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the ELM technique and brain learning. This book covers theories, algorithms, and applications of ELM. It gives readers a glance of the most recent advances of ELM.
Book Synopsis Advances in Information and Communication by : Kohei Arai
Download or read book Advances in Information and Communication written by Kohei Arai and published by Springer. This book was released on 2019-02-01 with total page 1074 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a remarkable collection of chapters that cover a wide range of topics in the areas of information and communication technologies and their real-world applications. It gathers the Proceedings of the Future of Information and Communication Conference 2019 (FICC 2019), held in San Francisco, USA from March 14 to 15, 2019. The conference attracted a total of 462 submissions from pioneering researchers, scientists, industrial engineers, and students from all around the world. Following a double-blind peer review process, 160 submissions (including 15 poster papers) were ultimately selected for inclusion in these proceedings. The papers highlight relevant trends in, and the latest research on: Communication, Data Science, Ambient Intelligence, Networking, Computing, Security, and the Internet of Things. Further, they address all aspects of Information Science and communication technologies, from classical to intelligent, and both the theory and applications of the latest technologies and methodologies. Gathering chapters that discuss state-of-the-art intelligent methods and techniques for solving real-world problems, along with future research directions, the book represents both an interesting read and a valuable asset.
Book Synopsis Advances in Neuroergonomics and Cognitive Engineering by : Hasan Ayaz
Download or read book Advances in Neuroergonomics and Cognitive Engineering written by Hasan Ayaz and published by Springer Nature. This book was released on 2020-06-27 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers broad overview of the field of cognitive engineering and neuroergonomics, covering emerging practices and future trends toward the harmonious integration of human operators and computer systems. It presents novel theoretical findings on mental workload and stress, activity theory, human reliability, error and risk, and a wealth of cutting-edge applications, such as strategies to make assistive technologies more user-oriented. Further, the book describes key advances in our understanding of cognitive processes, including mechanisms of perception, memory, reasoning, and motor response, with a particular focus on their role in interactions between humans and other elements of computer-based systems. Gathering the proceedings of the AHFE 2020 Virtual Conferences on Neuroergonomics and Cognitive Engineering, and Industrial Cognitive Ergonomics and Engineering Psychology, held on 16–20 July 2020, this book provides extensive and timely information for human–computer interaction researchers, human factors engineers and interaction designers, as well as decision-makers.
Book Synopsis Big Data Analytics for Sensor-Network Collected Intelligence by : Hui-Huang Hsu
Download or read book Big Data Analytics for Sensor-Network Collected Intelligence written by Hui-Huang Hsu and published by Morgan Kaufmann. This book was released on 2017-02-02 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Analytics for Sensor-Network Collected Intelligence explores state-of-the-art methods for using advanced ICT technologies to perform intelligent analysis on sensor collected data. The book shows how to develop systems that automatically detect natural and human-made events, how to examine people's behaviors, and how to unobtrusively provide better services. It begins by exploring big data architecture and platforms, covering the cloud computing infrastructure and how data is stored and visualized. The book then explores how big data is processed and managed, the key security and privacy issues involved, and the approaches used to ensure data quality. In addition, readers will find a thorough examination of big data analytics, analyzing statistical methods for data analytics and data mining, along with a detailed look at big data intelligence, ubiquitous and mobile computing, and designing intelligence system based on context and situation. Indexing: The books of this series are submitted to EI-Compendex and SCOPUS - Contains contributions from noted scholars in computer science and electrical engineering from around the globe - Provides a broad overview of recent developments in sensor collected intelligence - Edited by a team comprised of leading thinkers in big data analytics
Book Synopsis Advanced Machine Vision Paradigms for Medical Image Analysis by : Tapan K. Gandhi
Download or read book Advanced Machine Vision Paradigms for Medical Image Analysis written by Tapan K. Gandhi and published by Academic Press. This book was released on 2020-08-11 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs. - Explores major emerging trends in technology which are supporting the current advancement of medical image analysis with the help of computational intelligence - Highlights the advancement of conventional approaches in the field of medical image processing - Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques, as well as their applications in medical image analysis
Book Synopsis Proceedings of ELM-2015 Volume 1 by : Jiuwen Cao
Download or read book Proceedings of ELM-2015 Volume 1 written by Jiuwen Cao and published by Springer. This book was released on 2015-12-31 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains some selected papers from the International Conference on Extreme Learning Machine 2015, which was held in Hangzhou, China, December 15-17, 2015. This conference brought together researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the Extreme Learning Machine (ELM) technique and brain learning. This book covers theories, algorithms ad applications of ELM. It gives readers a glance of the most recent advances of ELM.
Book Synopsis Proceedings of ELM2019 by : Jiuwen Cao
Download or read book Proceedings of ELM2019 written by Jiuwen Cao and published by Springer Nature. This book was released on 2020-09-11 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains some selected papers from the International Conference on Extreme Learning Machine 2019, which was held in Yangzhou, China, December 14–16, 2019. Extreme Learning Machines (ELMs) aim to enable pervasive learning and pervasive intelligence. As advocated by ELM theories, it is exciting to see the convergence of machine learning and biological learning from the long-term point of view. ELM may be one of the fundamental ‘learning particles’ filling the gaps between machine learning and biological learning (of which activation functions are even unknown). ELM represents a suite of (machine and biological) learning techniques in which hidden neurons need not be tuned: inherited from their ancestors or randomly generated. ELM learning theories show that effective learning algorithms can be derived based on randomly generated hidden neurons (biological neurons, artificial neurons, wavelets, Fourier series, etc) as long as they are nonlinear piecewise continuous, independent of training data and application environments. Increasingly, evidence from neuroscience suggests that similar principles apply in biological learning systems. ELM theories and algorithms argue that “random hidden neurons” capture an essential aspect of biological learning mechanisms as well as the intuitive sense that the efficiency of biological learning need not rely on computing power of neurons. ELM theories thus hint at possible reasons why the brain is more intelligent and effective than current computers. The main theme of ELM2019 is Hierarchical ELM, AI for IoT, Synergy of Machine Learning and Biological Learning. This conference provides a forum for academics, researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the ELM technique and brain learning. This book covers theories, algorithms and applications of ELM. It gives readers a glance of the most recent advances of ELM.
Book Synopsis Bioinspired Optimization Methods and Their Applications by : Bogdan Filipič
Download or read book Bioinspired Optimization Methods and Their Applications written by Bogdan Filipič and published by Springer Nature. This book was released on 2020-11-16 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 9th International Conference on Bioinspired Optimization Methods and Their Applications, BIOMA 2020, held in Brussels, Belgium, in November 2020. The 24 full papers presented in this book were carefully reviewed and selected from 68 submissions. The papers in this BIOMA proceedings specialized in bioinspired algorithms as a means for solving the optimization problems and came in two categories: theoretical studies and methodology advancements on the one hand, and algorithm adjustments and their applications on the other. Due to the Corona pandemic BIOMA 2020 was held as a virtual event.
Book Synopsis Recent Trends in Image Processing and Pattern Recognition by : K. C. Santosh
Download or read book Recent Trends in Image Processing and Pattern Recognition written by K. C. Santosh and published by Springer. This book was released on 2019-07-19 with total page 744 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three-volume set constitutes the refereed proceedings of the Second International Conference on Recent Trends in Image Processing and Pattern Recognition (RTIP2R) 2018, held in Solapur, India, in December 2018. The 173 revised full papers presented were carefully reviewed and selected from 374 submissions. The papers are organized in topical sections in the tree volumes. Part I: computer vision and pattern recognition; machine learning and applications; and image processing. Part II: healthcare and medical imaging; biometrics and applications. Part III: document image analysis; image analysis in agriculture; and data mining, information retrieval and applications.
Book Synopsis Proceedings of ELM 2018 by : Jiuwen Cao
Download or read book Proceedings of ELM 2018 written by Jiuwen Cao and published by Springer. This book was released on 2019-06-29 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains some selected papers from the International Conference on Extreme Learning Machine 2018, which was held in Singapore, November 21–23, 2018. This conference provided a forum for academics, researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the ELM technique and brain learning. Extreme Learning Machines (ELM) aims to enable pervasive learning and pervasive intelligence. As advocated by ELM theories, it is exciting to see the convergence of machine learning and biological learning from the long-term point of view. ELM may be one of the fundamental “learning particles” filling the gaps between machine learning and biological learning (of which activation functions are even unknown). ELM represents a suite of (machine and biological) learning techniques in which hidden neurons need not be tuned: inherited from their ancestors or randomly generated. ELM learning theories show that effective learning algorithms can be derived based on randomly generated hidden neurons (biological neurons, artificial neurons, wavelets, Fourier series, etc.) as long as they are nonlinear piecewise continuous, independent of training data and application environments. Increasingly, evidence from neuroscience suggests that similar principles apply in biological learning systems. ELM theories and algorithms argue that “random hidden neurons” capture an essential aspect of biological learning mechanisms as well as the intuitive sense that the efficiency of biological learning need not rely on computing power of neurons. ELM theories thus hint at possible reasons why the brain is more intelligent and effective than current computers. The main theme of ELM2018 is Hierarchical ELM, AI for IoT, Synergy of Machine Learning and Biological Learning. This book covers theories, algorithms and applications of ELM. It gives readers a glance at the most recent advances of ELM.
Book Synopsis Intelligent Computing Theories and Application by : De-Shuang Huang
Download or read book Intelligent Computing Theories and Application written by De-Shuang Huang and published by Springer Nature. This book was released on 2020-10-13 with total page 614 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set of LNCS 12463 and LNCS 12464 constitutes - in conjunction with the volume LNAI 12465 - the refereed proceedings of the 16th International Conference on Intelligent Computing, ICIC 2020, held in Bari, Italy, in October 2020. The 162 full papers of the three proceedings volumes were carefully reviewed and selected from 457 submissions. The ICIC theme unifies the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. The theme for this conference is “Advanced Intelligent Computing Methodologies and Applications.” Papers related to this theme are especially solicited, addressing theories, methodologies, and applications in science and technology.
Book Synopsis Large-scale Kernel Machines by : Léon Bottou
Download or read book Large-scale Kernel Machines written by Léon Bottou and published by MIT Press. This book was released on 2007 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solutions for learning from large scale datasets, including kernel learning algorithms that scale linearly with the volume of the data and experiments carried out on realistically large datasets. Pervasive and networked computers have dramatically reduced the cost of collecting and distributing large datasets. In this context, machine learning algorithms that scale poorly could simply become irrelevant. We need learning algorithms that scale linearly with the volume of the data while maintaining enough statistical efficiency to outperform algorithms that simply process a random subset of the data. This volume offers researchers and engineers practical solutions for learning from large scale datasets, with detailed descriptions of algorithms and experiments carried out on realistically large datasets. At the same time it offers researchers information that can address the relative lack of theoretical grounding for many useful algorithms. After a detailed description of state-of-the-art support vector machine technology, an introduction of the essential concepts discussed in the volume, and a comparison of primal and dual optimization techniques, the book progresses from well-understood techniques to more novel and controversial approaches. Many contributors have made their code and data available online for further experimentation. Topics covered include fast implementations of known algorithms, approximations that are amenable to theoretical guarantees, and algorithms that perform well in practice but are difficult to analyze theoretically. Contributors Léon Bottou, Yoshua Bengio, Stéphane Canu, Eric Cosatto, Olivier Chapelle, Ronan Collobert, Dennis DeCoste, Ramani Duraiswami, Igor Durdanovic, Hans-Peter Graf, Arthur Gretton, Patrick Haffner, Stefanie Jegelka, Stephan Kanthak, S. Sathiya Keerthi, Yann LeCun, Chih-Jen Lin, Gaëlle Loosli, Joaquin Quiñonero-Candela, Carl Edward Rasmussen, Gunnar Rätsch, Vikas Chandrakant Raykar, Konrad Rieck, Vikas Sindhwani, Fabian Sinz, Sören Sonnenburg, Jason Weston, Christopher K. I. Williams, Elad Yom-Tov
