Proceedings Of Elm 2015 Volume 2

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Proceedings of ELM-2015 Volume 2

Jiuwen Cao,Kezhi Mao,Jonathan Wu,Amaury Lendasse
Proceedings of ELM 2015 Volume 2 Book PDF

Author : Jiuwen Cao,Kezhi Mao,Jonathan Wu,Amaury Lendasse
Publisher : Springer
Page : 516 pages
File Size : 54,8 Mb
Release : 2016-01-02
Category : Technology & Engineering
ISBN : 9783319283739

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Proceedings of ELM-2015 Volume 2 by Jiuwen Cao,Kezhi Mao,Jonathan Wu,Amaury Lendasse Pdf

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.

Proceedings of ELM-2015 Volume 1

Jiuwen Cao,Kezhi Mao,Jonathan Wu,Amaury Lendasse
Proceedings of ELM 2015 Volume 1 Book PDF

Author : Jiuwen Cao,Kezhi Mao,Jonathan Wu,Amaury Lendasse
Publisher : Springer
Page : 532 pages
File Size : 52,8 Mb
Release : 2015-12-31
Category : Technology & Engineering
ISBN : 9783319283975

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Proceedings of ELM-2015 Volume 1 by Jiuwen Cao,Kezhi Mao,Jonathan Wu,Amaury Lendasse Pdf

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.

Proceedings of ELM-2014 Volume 2

Jiuwen Cao,Kezhi Mao,Erik Cambria,Zhihong Man,Kar-Ann Toh
Proceedings of ELM 2014 Volume 2 Book PDF

Author : Jiuwen Cao,Kezhi Mao,Erik Cambria,Zhihong Man,Kar-Ann Toh
Publisher : Springer
Page : 400 pages
File Size : 50,5 Mb
Release : 2014-12-09
Category : Technology & Engineering
ISBN : 9783319140667

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Proceedings of ELM-2014 Volume 2 by Jiuwen Cao,Kezhi Mao,Erik Cambria,Zhihong Man,Kar-Ann Toh Pdf

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.

Proceedings of ELM-2016

Jiuwen Cao,Erik Cambria,Amaury Lendasse,Yoan Miche,Chi Man Vong
Proceedings of ELM 2016 Book PDF

Author : Jiuwen Cao,Erik Cambria,Amaury Lendasse,Yoan Miche,Chi Man Vong
Publisher : Springer
Page : 285 pages
File Size : 42,9 Mb
Release : 2017-05-25
Category : Technology & Engineering
ISBN : 9783319574219

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Proceedings of ELM-2016 by Jiuwen Cao,Erik Cambria,Amaury Lendasse,Yoan Miche,Chi Man Vong Pdf

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.

Proceedings of ELM2019

Jiuwen Cao,Chi Man Vong,Yoan Miche,Amaury Lendasse
Proceedings of ELM2019 Book PDF

Author : Jiuwen Cao,Chi Man Vong,Yoan Miche,Amaury Lendasse
Publisher : Springer Nature
Page : 189 pages
File Size : 51,9 Mb
Release : 2020-09-11
Category : Technology & Engineering
ISBN : 9783030589899

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Proceedings of ELM2019 by Jiuwen Cao,Chi Man Vong,Yoan Miche,Amaury Lendasse Pdf

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.

Imaging: Sensors and Technologies

Gonzalo Pajares Martinsanz
Imaging Sensors and Technologies Book PDF

Author : Gonzalo Pajares Martinsanz
Publisher : MDPI
Page : 635 pages
File Size : 42,7 Mb
Release : 2018-07-06
Category : Science (General)
ISBN : 9783038423607

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Imaging: Sensors and Technologies by Gonzalo Pajares Martinsanz Pdf

This book is a printed edition of the Special Issue "Imaging: Sensors and Technologies" that was published in Sensors

Computer Vision, Imaging and Computer Graphics Theory and Applications

Dominique Bechmann,Manuela Chessa,Ana Paula Cláudio,Francisco Imai,Andreas Kerren,Paul Richard,Alexandru Telea,Alain Tremeau
Computer Vision Imaging and Computer Graphics Theory and Applications Book PDF

Author : Dominique Bechmann,Manuela Chessa,Ana Paula Cláudio,Francisco Imai,Andreas Kerren,Paul Richard,Alexandru Telea,Alain Tremeau
Publisher : Springer
Page : 392 pages
File Size : 42,8 Mb
Release : 2019-07-23
Category : Computers
ISBN : 9783030267568

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Computer Vision, Imaging and Computer Graphics Theory and Applications by Dominique Bechmann,Manuela Chessa,Ana Paula Cláudio,Francisco Imai,Andreas Kerren,Paul Richard,Alexandru Telea,Alain Tremeau Pdf

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.

Artificial Neural Networks and Machine Learning – ICANN 2017

Alessandra Lintas,Stefano Rovetta,Paul F.M.J. Verschure,Alessandro E.P. Villa
Artificial Neural Networks and Machine Learning ICANN 2017 Book PDF

Author : Alessandra Lintas,Stefano Rovetta,Paul F.M.J. Verschure,Alessandro E.P. Villa
Publisher : Springer
Page : 815 pages
File Size : 44,6 Mb
Release : 2017-10-24
Category : Computers
ISBN : 9783319686127

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Artificial Neural Networks and Machine Learning – ICANN 2017 by Alessandra Lintas,Stefano Rovetta,Paul F.M.J. Verschure,Alessandro E.P. Villa Pdf

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.

Computational Science and Its Applications – ICCSA 2017

Osvaldo Gervasi,Beniamino Murgante,Sanjay Misra,Giuseppe Borruso,Carmelo M. Torre,Ana Maria A.C. Rocha,David Taniar,Bernady O. Apduhan,Elena Stankova,Alfredo Cuzzocrea
Computational Science and Its Applications ICCSA 2017 Book PDF

Author : Osvaldo Gervasi,Beniamino Murgante,Sanjay Misra,Giuseppe Borruso,Carmelo M. Torre,Ana Maria A.C. Rocha,David Taniar,Bernady O. Apduhan,Elena Stankova,Alfredo Cuzzocrea
Publisher : Springer
Page : 825 pages
File Size : 46,7 Mb
Release : 2017-07-14
Category : Computers
ISBN : 9783319624075

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Computational Science and Its Applications – ICCSA 2017 by Osvaldo Gervasi,Beniamino Murgante,Sanjay Misra,Giuseppe Borruso,Carmelo M. Torre,Ana Maria A.C. Rocha,David Taniar,Bernady O. Apduhan,Elena Stankova,Alfredo Cuzzocrea Pdf

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.

Proceedings of ELM 2018

Jiuwen Cao,Chi Man Vong,Yoan Miche,Amaury Lendasse
Proceedings of ELM 2018 Book PDF

Author : Jiuwen Cao,Chi Man Vong,Yoan Miche,Amaury Lendasse
Publisher : Springer
Page : 347 pages
File Size : 55,5 Mb
Release : 2019-06-29
Category : Technology & Engineering
ISBN : 9783030233075

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Proceedings of ELM 2018 by Jiuwen Cao,Chi Man Vong,Yoan Miche,Amaury Lendasse Pdf

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.

Proceedings of ELM-2017

Jiuwen Cao,Chi Man Vong,Yoan Miche,Amaury Lendasse
Proceedings of ELM 2017 Book PDF

Author : Jiuwen Cao,Chi Man Vong,Yoan Miche,Amaury Lendasse
Publisher : Springer
Page : 340 pages
File Size : 42,6 Mb
Release : 2018-10-16
Category : Technology & Engineering
ISBN : 9783030015206

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Proceedings of ELM-2017 by Jiuwen Cao,Chi Man Vong,Yoan Miche,Amaury Lendasse Pdf

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.

Machine Learning and Deep Learning in Real-Time Applications

Mahrishi, Mehul,Hiran, Kamal Kant,Meena, Gaurav,Sharma, Paawan
Machine Learning and Deep Learning in Real Time Applications Book PDF

Author : Mahrishi, Mehul,Hiran, Kamal Kant,Meena, Gaurav,Sharma, Paawan
Publisher : IGI Global
Page : 344 pages
File Size : 45,8 Mb
Release : 2020-04-24
Category : Computers
ISBN : 9781799830979

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Machine Learning and Deep Learning in Real-Time Applications by Mahrishi, Mehul,Hiran, Kamal Kant,Meena, Gaurav,Sharma, Paawan Pdf

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.

International Conference on Innovative Computing and Communications

Aboul Ella Hassanien,Oscar Castillo,Sameer Anand,Ajay Jaiswal
International Conference on Innovative Computing and Communications Book PDF

Author : Aboul Ella Hassanien,Oscar Castillo,Sameer Anand,Ajay Jaiswal
Publisher : Springer Nature
Page : 886 pages
File Size : 49,7 Mb
Release : 2023-07-25
Category : Technology & Engineering
ISBN : 9789819933150

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International Conference on Innovative Computing and Communications by Aboul Ella Hassanien,Oscar Castillo,Sameer Anand,Ajay Jaiswal Pdf

This book includes high-quality research papers presented at the Sixth International Conference on Innovative Computing and Communication (ICICC 2023), which is held at the Shaheed Sukhdev College of Business Studies, University of Delhi, Delhi, India, on February 17–18, 2023. Introducing the innovative works of scientists, professors, research scholars, students and industrial experts in the field of computing and communication, the book promotes the transformation of fundamental research into institutional and industrialized research and the conversion of applied exploration into real-time applications.

Machine Learning, Big Data, and IoT for Medical Informatics

Pardeep Kumar,Yugal Kumar,Mohamed A. Tawhid
Machine Learning Big Data and IoT for Medical Informatics Book PDF

Author : Pardeep Kumar,Yugal Kumar,Mohamed A. Tawhid
Publisher : Academic Press
Page : 458 pages
File Size : 44,7 Mb
Release : 2021-06-13
Category : Computers
ISBN : 9780128217818

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Machine Learning, Big Data, and IoT for Medical Informatics by Pardeep Kumar,Yugal Kumar,Mohamed A. Tawhid Pdf

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.

NoSQL Data Models

Olivier Pivert
NoSQL Data Models Book PDF

Author : Olivier Pivert
Publisher : John Wiley & Sons
Page : 278 pages
File Size : 51,7 Mb
Release : 2018-07-30
Category : Computers
ISBN : 9781119544142

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NoSQL Data Models by Olivier Pivert Pdf

The topic of NoSQL databases has recently emerged, to face the Big Data challenge, namely the ever increasing volume of data to be handled. It is now recognized that relational databases are not appropriate in this context, implying that new database models and techniques are needed. This book presents recent research works, covering the following basic aspects: semantic data management, graph databases, and big data management in cloud environments. The chapters in this book report on research about the evolution of basic concepts such as data models, query languages, and new challenges regarding implementation issues.