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Pyramidal Neural Networks

Pyramidal Neural Networks PDF Author: Horst Bischof
Publisher: Psychology Press
ISBN: 9780805819144
Category : Computers
Languages : en
Pages : 220

Book Description
A large amount of information about the world we live in is supplied by our visual systems. Humans perform the task of vision effortlessly without being aware of this complex process. Hierarchical structures permit successful examination of such intricate operations. This book investigates hierarchical-structured neural networks for vision and image processing tasks and proposes various new neural network models for that purpose. It exploits the capabilities of hierarchical neural networks in a systematic way by considering the similarities to hierarchical structures already in use by computer vision researchers. All issues of hierarchical neural networks are treated in considerable detail; that is, the structure of the network, the representation issue, and learning mechanisms are analyzed theoretically as well as experimentally. Considering the similarity between conventional vision algorithms and hierarchical neural networks not only allows a transfer of knowledge between these two fields, but also gives voice to many new algorithms.

Pyramidal Neural Networks

Pyramidal Neural Networks PDF Author: Horst Bischof
Publisher: Psychology Press
ISBN: 9780805819144
Category : Computers
Languages : en
Pages : 220

Book Description
A large amount of information about the world we live in is supplied by our visual systems. Humans perform the task of vision effortlessly without being aware of this complex process. Hierarchical structures permit successful examination of such intricate operations. This book investigates hierarchical-structured neural networks for vision and image processing tasks and proposes various new neural network models for that purpose. It exploits the capabilities of hierarchical neural networks in a systematic way by considering the similarities to hierarchical structures already in use by computer vision researchers. All issues of hierarchical neural networks are treated in considerable detail; that is, the structure of the network, the representation issue, and learning mechanisms are analyzed theoretically as well as experimentally. Considering the similarity between conventional vision algorithms and hierarchical neural networks not only allows a transfer of knowledge between these two fields, but also gives voice to many new algorithms.

Neural Information Processing

Neural Information Processing PDF Author: Irwin King
Publisher: Springer Science & Business Media
ISBN: 3540464816
Category : Computers
Languages : en
Pages : 1225

Book Description
The three volume set LNCS 4232, LNCS 4233, and LNCS 4234 constitutes the refereed proceedings of the 13th International Conference on Neural Information Processing, ICONIP 2006, held in Hong Kong, China in October 2006. The 386 revised full papers presented were carefully reviewed and selected from 1175 submissions.

Neural Networks and Psychopathology

Neural Networks and Psychopathology PDF Author: Dan J. Stein
Publisher: Cambridge University Press
ISBN: 1139429256
Category : Medical
Languages : en
Pages : 387

Book Description
Research on connectionist models is one of the most exciting areas in cognitive science, and neural network models of psychopathology have immediate theoretical and empirical appeal. The contributors to this study review theoretical, historical and clinical issues, including the contribution of neural network models to diagnosis, pharmacotherapy and psychotherapy. Models are presented for a range of disorders, including schizophrenia, obsessive-compulsive disorder, dissociative phenomena, autism and Alzheimer's disease. This book will appeal to a broad audience. On the one hand, it will be read with interest by psychiatrists, psychologists and other clinicians and researchers in psychopathology. On the other, it will appeal to those working in cognitive science and artificial intelligence, and particularly those interested in neural network or connectionist models.

Advances in Neural Networks

Advances in Neural Networks PDF Author: Simone Bassis
Publisher: Springer
ISBN: 3319337475
Category : Technology & Engineering
Languages : en
Pages : 539

Book Description
This carefully edited book is putting emphasis on computational and artificial intelligent methods for learning and their relative applications in robotics, embedded systems, and ICT interfaces for psychological and neurological diseases. The book is a follow-up of the scientific workshop on Neural Networks (WIRN 2015) held in Vietri sul Mare, Italy, from the 20th to the 22nd of May 2015. The workshop, at its 27th edition became a traditional scientific event that brought together scientists from many countries, and several scientific disciplines. Each chapter is an extended version of the original contribution presented at the workshop, and together with the reviewers’ peer revisions it also benefits from the live discussion during the presentation. The content of book is organized in the following sections. 1. Introduction, 2. Machine Learning, 3. Artificial Neural Networks: Algorithms and models, 4. Intelligent Cyberphysical and Embedded System, 5. Computational Intelligence Methods for Biomedical ICT in Neurological Diseases, 6. Neural Networks-Based Approaches to Industrial Processes, 7. Reconfigurable Modular Adaptive Smart Robotic Systems for Optoelectronics Industry: The White'R Instantiation This book is unique in proposing a holistic and multidisciplinary approach to implement autonomous, and complex Human Computer Interfaces.

Artificial Neural Networks and Machine Learning -- ICANN 2014

Artificial Neural Networks and Machine Learning -- ICANN 2014 PDF Author: Stefan Wermter
Publisher: Springer
ISBN: 3319111795
Category : Computers
Languages : en
Pages : 852

Book Description
The book constitutes the proceedings of the 24th International Conference on Artificial Neural Networks, ICANN 2014, held in Hamburg, Germany, in September 2014. The 107 papers included in the proceedings were carefully reviewed and selected from 173 submissions. The focus of the papers is on following topics: recurrent networks; competitive learning and self-organisation; clustering and classification; trees and graphs; human-machine interaction; deep networks; theory; reinforcement learning and action; vision; supervised learning; dynamical models and time series; neuroscience; and applications.

Advances in Neural Networks-isnn 2006

Advances in Neural Networks-isnn 2006 PDF Author:
Publisher: Springer Science & Business Media
ISBN: 354034439X
Category : Artificial intelligence
Languages : en
Pages : 1507

Book Description


Advances in Neural Networks

Advances in Neural Networks PDF Author: Fuchun Sun
Publisher: Springer Science & Business Media
ISBN: 3540877312
Category : Computers
Languages : en
Pages : 939

Book Description
(Bayreuth University, Germany), Jennie Si (Arizona State University, USA), and Hang Li (MicrosoftResearchAsia, China). Besides the regularsessions andpanels, ISNN 2008 also featured four special sessions focusing on some emerging topics.

Plausible Neural Networks for Biological Modelling

Plausible Neural Networks for Biological Modelling PDF Author: H.A. Mastebroek
Publisher: Springer Science & Business Media
ISBN: 9780792371922
Category : Computers
Languages : en
Pages : 276

Book Description
This book has the unique intention of returning the mathematical tools of neural networks to the biological realm of the nervous system, where they originated a few decades ago. It aims to introduce, in a didactic manner, two relatively recent developments in neural network methodology, namely recurrence in the architecture and the use of spiking or integrate-and-fire neurons. In addition, the neuro-anatomical processes of synapse modification during development, training, and memory formation are discussed as realistic bases for weight-adjustment in neural networks. While neural networks have many applications outside biology, where it is irrelevant precisely which architecture and which algorithms are used, it is essential that there is a close relationship between the network's properties and whatever is the case in a neuro-biological phenomenon that is being modelled or simulated in terms of a neural network. A recurrent architecture, the use of spiking neurons and appropriate weight update rules contribute to the plausibility of a neural network in such a case. Therefore, in the first half of this book the foundations are laid for the application of neural networks as models for the various biological phenomena that are treated in the second half of this book. These include various neural network models of sensory and motor control tasks that implement one or several of the requirements for biological plausibility.

Artificial Neural Networks and Machine Learning – ICANN 2017

Artificial Neural Networks and Machine Learning – ICANN 2017 PDF Author: Alessandra Lintas
Publisher: Springer
ISBN: 3319686003
Category : Computers
Languages : en
Pages : 469

Book Description
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.

Advances in Neural Networks- ISNN 2013

Advances in Neural Networks- ISNN 2013 PDF Author: Chengan Guo
Publisher: Springer
ISBN: 364239065X
Category : Computers
Languages : en
Pages : 687

Book Description
The two-volume set LNCS 7951 and 7952 constitutes the refereed proceedings of the 10th International Symposium on Neural Networks, ISNN 2013, held in Dalian, China, in July 2013. The 157 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in following topics: computational neuroscience, cognitive science, neural network models, learning algorithms, stability and convergence analysis, kernel methods, large margin methods and SVM, optimization algorithms, varational methods, control, robotics, bioinformatics and biomedical engineering, brain-like systems and brain-computer interfaces, data mining and knowledge discovery and other applications of neural networks.