Eighth International Work Conference On Artificial And Natural Neural Networks

Author: Joan Cabestany
Editor: Springer Science & Business Media
ISBN: 3540262083
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This book constitutes the refereed proceedings of the 8th International Workshop on Artificial Neural Networks, IWANN 2005, held in Vilanova i la Geltrú, Barcelona, Spain in June 2005. The 150 revised papers presented - including the contribution of three invited speakers - were carefully reviewed and selected from 240 submissions for inclusion in the book and address the following topics: mathematical and theoretical methods, evolutionary computation, neurocomputational inspired models, learning and adaptation, radial basic functions structures, self-organizing networks and methods, support vector machines, cellular neural networks, hybrid systems, neuroengineering and hardware implementations, pattern recognition, perception and robotics and applications in a broad variety of fields.

Advances In Neural Networks Isnn 2017

Author: Fengyu Cong
Editor: Springer
ISBN: 3319590812
File Size: 11,48 MB
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This book constitutes the refereed proceedings of the 14th International Symposium on Neural Networks, ISNN 2017, held in Sapporo, Hakodate, and Muroran, Hokkaido, Japan, in June 2017. The 135 revised full papers presented in this two-volume set were carefully reviewed and selected from 259 submissions. The papers cover topics like perception, emotion and development, action and motor control, attractor and associative memory, neurodynamics, complex systems, and chaos.

Ieee International Symposium On Industrial Electronics Proceedings

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Deep Learning In Medical Image Analysis And Multimodal Learning For Clinical Decision Support

Author: Danail Stoyanov
Editor: Springer
ISBN: 3030008894
File Size: 35,48 MB
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This book constitutes the refereed joint proceedings of the 4th International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2018, and the 8th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018. The 39 full papers presented at DLMIA 2018 and the 4 full papers presented at ML-CDS 2018 were carefully reviewed and selected from 85 submissions to DLMIA and 6 submissions to ML-CDS. The DLMIA papers focus on the design and use of deep learning methods in medical imaging. The ML-CDS papers discuss new techniques of multimodal mining/retrieval and their use in clinical decision support.

Proceedings Of The American Power Conference

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Intelligent Robots And Computer Vision

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File Size: 47,73 MB
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Neural Network Applications To Transportation

Author: Martin Laplante
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File Size: 19,85 MB
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This project was conducted to sensitize transportation managers to the capabilities of neural network implementations through the production of educational materials and to identify transportation applications where a neural network implementation would provide an appropriate solution. The document contains a tutorial-type introduction to neural networks and describes the major classes of applications and types of neural networks, categorized as classification, prediction, sensor fusion, optimization, control, storage, and new computing paradigms. About 100 potential applications were found, about 12 of which are singled out for more detailed analysis.

Neural Network Solutions For Trading In Financial Markets

Author: Dirk Emma Baestaens
Editor: Financial Times Management
ISBN:
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Offers an alternative technique in forecasting to the traditional techniques used in trading and dealing. The book explains the shortcomings of traditional techniques and shows how neural networks overcome many of the disadvantages of these traditional systems.

Neural Networks In Vision And Pattern Recognition

Author: J Skrzypek
Editor: World Scientific
ISBN: 9814505439
File Size: 64,37 MB
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The neural network paradigm with its various advantages might be the next promising bridge between artificial intelligence and pattern recognition that will help with the conceptualization of new computational artifacts. This volume contains ten papers which represent some of the work being done in the field, such as in computational neuroscience, pattern recognition, computational vision, and applications. Contents:Introduction (J Skrzypek & W Karplus)Lightness Constancy from Luminance Contrast (J Skrzypek & D Gungner)Bringing the Grandmother Back into the Picture: A Memory-Based View of Object Recognition (S Edelman & T Poggio)Internal Organization of Classifier Networks Trained by Backpropagation (D F Michaels)System Identification with Artificial Neural Networks (E R Tisdale & W J Karplus)Mixed Finite Element Based Neural Networks in Visual Reconstruction (D Suter)The Random Neural Network Model for Texture Generation (V Atalay et al.)Neural Networks for Collective Translational Invariant Object Recognition (L-W Chan)Image Recognition and Reconstruction Using Associative Magnetic Processing (J M Goodwin et al.)Incorporating Uncertainty in Neural Networks (B R Kämmerer)Neural Networks for the Recognition of Engraved Musical Scores (P Martin & C Bellissant) Readership: Computer scientists, engineers and neuroscientists. keywords:

Ecai 94 Proceedings

Author: A. G. Cohn
Editor: John Wiley & Sons Incorporated
ISBN:
File Size: 38,90 MB
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A collection of refereed papers presented at the 11th European Conference on Artificial Intelligence held in Amsterdam, The Netherlands in August 1994.

Progress In Neural Networks

Author: Omid M. Omidvar
Editor: Intellect Books
ISBN:
File Size: 34,52 MB
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This is a study of the use of neural networks for machine vision. It is part of a series which reviews research in natural and synthetic neural networks, as well as in modelling, analysis, design, and development of neural networks in software and hardware areas. Contributions from researchers and practitioners serve as a platform for discussion of topics of interest to the neural network and cognitive information processing communities.

Proceedings

Author: International Conference on Neural Networks 1995, Perth, Western Australia
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ISBN: 9780780327696
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Neural Networks For Conditional Probability Estimation

Author: Dirk Husmeier
Editor: Springer
ISBN:
File Size: 72,85 MB
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This volume presents a neural network architecture for the prediction of conditional probability densities - which is vital when carrying out universal approximation on variables which are either strongly skewed or multimodal. Two alternative approaches are discussed: the GM network, in which all parameters are adapted in the training scheme, and the GM-RVFL model which draws on the random functional link net approach. Points of particular interest are: - it examines the modification to standard approaches needed for conditional probability prediction; - it provides the first real-world test results for recent theoretical findings about the relationship between generalisation performance of committees and the over-flexibility of their members; This volume will be of interest to all researchers, practitioners and postgraduate / advanced undergraduate students working on applications of neural networks - especially those related to finance and pattern recognition.

The 1994 Ieee International Conference On Neural Networks

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Apl Conference Proceedings

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File Size: 32,38 MB
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Ssp

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File Size: 25,41 MB
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Neural Computation

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File Size: 20,92 MB
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Mobile Robots

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Advanced Neural Computers

Author: Rolf Eckmiller
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File Size: 60,16 MB
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This book is the outcome of the International Symposium on Neural Networks for Sensory and Motor Systems (NSMS) held in March 1990 in the FRG. The NSMS symposium assembled 45 invited experts from Europe, America and Japan representing the fields of Neuroinformatics, Computer Science, Computational Neuroscience, and Neuroscience. As a rapidly-published report on the state of the art in Neural Computing it forms a reference book for future research in this highly interdisciplinary field and should prove useful in the endeavor to transfer concepts of brain function and structure to novel neural computers with adaptive, dynamical neural net topologies. A feature of the book is the completeness of the references provided. An alphabetical list of all references quoted in the papers is given, as well as a separate list of general references to help newcomers to the field. A subject index and author index also facilitate access to various details.