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Proceedings Of Elm 2015 Volume 2
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Book Synopsis Proceedings of ELM-2015 Volume 2 by : Jiuwen Cao
Download or read book Proceedings of ELM-2015 Volume 2 written by Jiuwen Cao and published by Springer. This book was released on 2016-01-02 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 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 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 532 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 ELM-2016 by : Jiuwen Cao
Download or read book Proceedings of ELM-2016 written by Jiuwen Cao and published by Springer. This book was released on 2017-05-25 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains some selected papers from the International Conference on Extreme Learning Machine 2016, which was held in Singapore, December 13-15, 2016. This conference will provide 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 break the barriers between the conventional artificial learning techniques and biological learning mechanism. ELM represents a suite of (machine or possibly biological) learning techniques in which hidden neurons need not be tuned. ELM learning theories show that very effective learning algorithms can be derived based on randomly generated hidden neurons (with almost any nonlinear piecewise activation functions), 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. ELM offers significant advantages over conventional neural network learning algorithms such as fast learning speed, ease of implementation, and minimal need for human intervention. ELM also shows potential as a viable alternative technique for large‐scale computing and artificial intelligence. 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 Imaging: Sensors and Technologies by : Gonzalo Pajares Martinsanz
Download or read book Imaging: Sensors and Technologies written by Gonzalo Pajares Martinsanz and published by MDPI. This book was released on 2018-07-06 with total page 635 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Imaging: Sensors and Technologies" that was published in Sensors
Book Synopsis Computer Vision, Imaging and Computer Graphics Theory and Applications by : Dominique Bechmann
Download or read book Computer Vision, Imaging and Computer Graphics Theory and Applications written by Dominique Bechmann and published by Springer. This book was released on 2019-07-23 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes thoroughly revised and selected papers from the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2018, held in Funchal-Madeira, Portugal, in January 2018. The 18 thoroughly revised and extended papers presented in this volume were carefully reviewed and selected from 317 submissions. The papers contribute to the understanding of relevant trends of current research on computer graphics; human computer interaction; information visualization; computer vision.
Book Synopsis Artificial Neural Networks and Machine Learning – ICANN 2017 by : Alessandra Lintas
Download or read book Artificial Neural Networks and Machine Learning – ICANN 2017 written by Alessandra Lintas and published by Springer. This book was released on 2017-10-24 with total page 815 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two volume set, LNCS 10613 and 10614, constitutes the proceedings of then 26th International Conference on Artificial Neural Networks, ICANN 2017, held in Alghero, Italy, in September 2017. The 128 full papers included in this volume were carefully reviewed and selected from 270 submissions. They were organized in topical sections named: From Perception to Action; From Neurons to Networks; Brain Imaging; Recurrent Neural Networks; Neuromorphic Hardware; Brain Topology and Dynamics; Neural Networks Meet Natural and Environmental Sciences; Convolutional Neural Networks; Games and Strategy; Representation and Classification; Clustering; Learning from Data Streams and Time Series; Image Processing and Medical Applications; Advances in Machine Learning. There are 63 short paper abstracts that are included in the back matter of the volume.
Book Synopsis Computational Science and Its Applications – ICCSA 2017 by : Osvaldo Gervasi
Download or read book Computational Science and Its Applications – ICCSA 2017 written by Osvaldo Gervasi and published by Springer. This book was released on 2017-07-14 with total page 825 pages. Available in PDF, EPUB and Kindle. Book excerpt: The six-volume set LNCS 10404-10409 constitutes the refereed proceedings of the 17th International Conference on Computational Science and Its Applications, ICCSA 2017, held in Trieste, Italy, in July 2017. The 313 full papers and 12 short papers included in the 6-volume proceedings set were carefully reviewed and selected from 1052 submissions. Apart from the general tracks, ICCSA 2017 included 43 international workshops in various areas of computational sciences, ranging from computational science technologies to specific areas of computational sciences, such as computer graphics and virtual reality. Furthermore, this year ICCSA 2017 hosted the XIV International Workshop On Quantum Reactive Scattering. The program also featured 3 keynote speeches and 4 tutorials.
Book Synopsis AI and Machine Learning for Network and Security Management by : Yulei Wu
Download or read book AI and Machine Learning for Network and Security Management written by Yulei Wu and published by John Wiley & Sons. This book was released on 2022-11-08 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: AI AND MACHINE LEARNING FOR NETWORK AND SECURITY MANAGEMENT Extensive Resource for Understanding Key Tasks of Network and Security Management AI and Machine Learning for Network and Security Management covers a range of key topics of network automation for network and security management, including resource allocation and scheduling, network planning and routing, encrypted traffic classification, anomaly detection, and security operations. In addition, the authors introduce their large-scale intelligent network management and operation system and elaborate on how the aforementioned areas can be integrated into this system, plus how the network service can benefit. Sample ideas covered in this thought-provoking work include: How cognitive means, e.g., knowledge transfer, can help with network and security management How different advanced AI and machine learning techniques can be useful and helpful to facilitate network automation How the introduced techniques can be applied to many other related network and security management tasks Network engineers, content service providers, and cybersecurity service providers can use AI and Machine Learning for Network and Security Management to make better and more informed decisions in their areas of specialization. Students in a variety of related study programs will also derive value from the work by gaining a base understanding of historical foundational knowledge and seeing the key recent developments that have been made in the field.
Book Synopsis Proceedings of ELM-2017 by : Jiuwen Cao
Download or read book Proceedings of ELM-2017 written by Jiuwen Cao and published by Springer. This book was released on 2018-10-16 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains some selected papers from the International Conference on Extreme Learning Machine (ELM) 2017, held in Yantai, China, October 4–7, 2017. The book covers theories, algorithms and applications of ELM. 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 will provide 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. It gives readers a glance of the most recent advances of ELM.
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 Intelligence Science and Big Data Engineering. Image and Video Data Engineering by : Xiaofei He
Download or read book Intelligence Science and Big Data Engineering. Image and Video Data Engineering written by Xiaofei He and published by Springer. This book was released on 2015-10-13 with total page 661 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNCS 9242 + 9243 constitutes the proceedings of the 5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015, held in Suzhou, China, in June 2015. The total of 126 papers presented in the proceedings was carefully reviewed and selected from 416 submissions. They deal with big data, neural networks, image processing, computer vision, pattern recognition and graphics, object detection, dimensionality reduction and manifold learning, unsupervised learning and clustering, anomaly detection, semi-supervised learning.
Book Synopsis Machine Learning and Deep Learning in Real-Time Applications by : Mahrishi, Mehul
Download or read book Machine Learning and Deep Learning in Real-Time Applications written by Mahrishi, Mehul and published by IGI Global. This book was released on 2020-04-24 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence and its various components are rapidly engulfing almost every professional industry. Specific features of AI that have proven to be vital solutions to numerous real-world issues are machine learning and deep learning. These intelligent agents unlock higher levels of performance and efficiency, creating a wide span of industrial applications. However, there is a lack of research on the specific uses of machine/deep learning in the professional realm. Machine Learning and Deep Learning in Real-Time Applications provides emerging research exploring the theoretical and practical aspects of machine learning and deep learning and their implementations as well as their ability to solve real-world problems within several professional disciplines including healthcare, business, and computer science. Featuring coverage on a broad range of topics such as image processing, medical improvements, and smart grids, this book is ideally designed for researchers, academicians, scientists, industry experts, scholars, IT professionals, engineers, and students seeking current research on the multifaceted uses and implementations of machine learning and deep learning across the globe.
Book Synopsis Hybrid Artificial Intelligent Systems by : Francisco Javier Martínez de Pisón
Download or read book Hybrid Artificial Intelligent Systems written by Francisco Javier Martínez de Pisón and published by Springer. This book was released on 2017-06-12 with total page 725 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the refereed proceedings of the 12th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2017, held in La Rioja, Spain, in June 2017. The 60 full papers published in this volume were carefully reviewed and selected from 130 submissions. They are organized in the following topical sections: data mining, knowledge discovery and big data; bioinspired models and evolutionary computing; learning algorithms; visual analysis and advanced data processing techniques; data mining applications; and hybrid intelligent 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 347 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 Machine Learning, Big Data, and IoT for Medical Informatics by : Pardeep Kumar
Download or read book Machine Learning, Big Data, and IoT for Medical Informatics written by Pardeep Kumar and published by Academic Press. This book was released on 2021-06-13 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning, Big Data, and IoT for Medical Informatics focuses on the latest techniques adopted in the field of medical informatics. In medical informatics, machine learning, big data, and IOT-based techniques play a significant role in disease diagnosis and its prediction. In the medical field, the structure of data is equally important for accurate predictive analytics due to heterogeneity of data such as ECG data, X-ray data, and image data. Thus, this book focuses on the usability of machine learning, big data, and IOT-based techniques in handling structured and unstructured data. It also emphasizes on the privacy preservation techniques of medical data. This volume can be used as a reference book for scientists, researchers, practitioners, and academicians working in the field of intelligent medical informatics. In addition, it can also be used as a reference book for both undergraduate and graduate courses such as medical informatics, machine learning, big data, and IoT. Explains the uses of CNN, Deep Learning and extreme machine learning concepts for the design and development of predictive diagnostic systems. Includes several privacy preservation techniques for medical data. Presents the integration of Internet of Things with predictive diagnostic systems for disease diagnosis. Offers case studies and applications relating to machine learning, big data, and health care analysis.
