Improving the Generalization Ability of Neural Network Classifiers
Title | Improving the Generalization Ability of Neural Network Classifiers PDF eBook |
Author | Kailash L. Kalantri |
Publisher | |
Pages | 146 |
Release | 1992 |
Genre | Neural networks (Computer science) |
ISBN |
Advanced Computing, Networking and Security
Title | Advanced Computing, Networking and Security PDF eBook |
Author | P. Santhi Thilagam |
Publisher | Springer |
Pages | 656 |
Release | 2012-04-02 |
Genre | Computers |
ISBN | 3642292801 |
This book constitutes revised selected papers from the International Conference on Advanced Computing, Networking and Security, ADCONS 2011, held in Surathkal, India, in December 2011. The 73 papers included in this book were carefully reviewed and selected from 289 submissions. The papers are organized in topical sections on distributed computing, image processing, pattern recognition, applied algorithms, wireless networking, sensor networks, network infrastructure, cryptography, Web security, and application security.
Generalization With Deep Learning: For Improvement On Sensing Capability
Title | Generalization With Deep Learning: For Improvement On Sensing Capability PDF eBook |
Author | Zhenghua Chen |
Publisher | World Scientific |
Pages | 327 |
Release | 2021-04-07 |
Genre | Computers |
ISBN | 9811218854 |
Deep Learning has achieved great success in many challenging research areas, such as image recognition and natural language processing. The key merit of deep learning is to automatically learn good feature representation from massive data conceptually. In this book, we will show that the deep learning technology can be a very good candidate for improving sensing capabilities.In this edited volume, we aim to narrow the gap between humans and machines by showcasing various deep learning applications in the area of sensing. The book will cover the fundamentals of deep learning techniques and their applications in real-world problems including activity sensing, remote sensing and medical sensing. It will demonstrate how different deep learning techniques help to improve the sensing capabilities and enable scientists and practitioners to make insightful observations and generate invaluable discoveries from different types of data.
New Approaches for Improving the Performance of Neural Network Classifiers
Title | New Approaches for Improving the Performance of Neural Network Classifiers PDF eBook |
Author | Srivathsan Padmanabha-Baghavan |
Publisher | |
Pages | 148 |
Release | 1997 |
Genre | Back propagation (Artificial intelligence) |
ISBN |
Radial Basis functions and Backpropagation learning algorithm are compared for speed and generalization performance of neural networks. Procedures were aided by advance mathematical and statistical concepts like Kohonen's algorithm for improving machine intelligence.
Techniques for the Improvement of Generalization Capabilities of Neural Networks
Title | Techniques for the Improvement of Generalization Capabilities of Neural Networks PDF eBook |
Author | Alice V. Ling |
Publisher | |
Pages | 252 |
Release | 1989 |
Genre | Artificial intelligence |
ISBN |
Support Vector Machines for Pattern Classification
Title | Support Vector Machines for Pattern Classification PDF eBook |
Author | Shigeo Abe |
Publisher | Springer Science & Business Media |
Pages | 486 |
Release | 2010-07-23 |
Genre | Technology & Engineering |
ISBN | 1849960984 |
A guide on the use of SVMs in pattern classification, including a rigorous performance comparison of classifiers and regressors. The book presents architectures for multiclass classification and function approximation problems, as well as evaluation criteria for classifiers and regressors. Features: Clarifies the characteristics of two-class SVMs; Discusses kernel methods for improving the generalization ability of neural networks and fuzzy systems; Contains ample illustrations and examples; Includes performance evaluation using publicly available data sets; Examines Mahalanobis kernels, empirical feature space, and the effect of model selection by cross-validation; Covers sparse SVMs, learning using privileged information, semi-supervised learning, multiple classifier systems, and multiple kernel learning; Explores incremental training based batch training and active-set training methods, and decomposition techniques for linear programming SVMs; Discusses variable selection for support vector regressors.
Improving Generalization Capability of Neural Networks Through Complexity Regularization
Title | Improving Generalization Capability of Neural Networks Through Complexity Regularization PDF eBook |
Author | Chooi Mey Kwan |
Publisher | |
Pages | |
Release | 1999 |
Genre | Neural networks (Computer science) |
ISBN |