1,721,040 research outputs found
Book Review: Differential Neural Networks for Robust Nonlinear Control by A.S. Poznyak, E.N. Sanchez and Wen Yu
No full textA SVM GREEK CHARACTER RECOGNISER
No full textABSTRACT
This paper presents a handwritten Greek character recognizer based
on Support Vector Machines (SVMs) . The recognizer is composed of
two modules: the first one is a feature extractor, the second one, the
classifier, is performed by means of SVMs. The recognizer, tested on a database of more than 22000 handwritten Greek characters, has shown
satisfactory performances. SVMs compare notably better, in terms of
recognition rates, with popular neural classifiers, such as Learning Vector Quantization and Multi-layer Perceptron
Book Review: Nonlinear Predictive Control, Theory and Practice by B. Kouvaritakis and M. Cannon
No full textBook Review: Information Dynamics: foundations and applications by G. Deco and B. Schurmann
No full textBOOK REVIEW: Image Processing: Principles and Applications by Tinku Acharaya, Ajoy K. Ray
No full textData Dimensionality Estimation Methods: A Survey
No full textIn this paper, data dimensionality estimation methods are reviewed. The estimation of the dimensionality of a data set is a classical problem of pattern recognition. There are some good reviews (Algorithms for Clustering Data, Prentice-Hall, Englewood Cliffs, NJ, 1988) in literature but they do not include more recent developments based on fractal techniques and neural autoassociators. The aim of this paper is to provide an up-to-date survey of the dimensionality estimation methods of a data set, paying special attention to the fractal-based methods
Machine Learning for Audio, Image and Video Analysis: Theory and Applications
No full textNo abstract available
Handy: A real-time three color glove-based gesture recognizer with learning vector quantization
No full textThis paper presents Handy, a real-time hand gesture recognizer based on a three color glove. The recognizer is formed by three modules. The first module, fed by the frame acquired by a webcam, identifies the hand image in the scene. The second module, a feature extractor, represents the image by a nine-dimensional feature vector. The third module, the classifier, is performed by means of learning vector quantization. The recognizer, tested on a dataset of 907 hand gestures, has shown very high recognition rate
Machine Learning for Image, Video and Audio Analysis
No full textABSTRACT
Machine Learning involves several scientific domains including mathematics, computer science, statistics and biology, and is an approach that enables computers to automatically learn from data. Focusing on complex media and how to convert raw data into useful information, this book offers both introductory and advanced material in the combined fields of machine learning and image/video processing.
The machine learning techniques presented enable readers to address many real world problems involving complex data. Examples covering areas such as automatic speech and handwriting transcription, automatic face recognition, and semantic video segmentation are included, along with detailed introductions to algorithms and examples of their applications.
The book is organized in four parts: The first focuses on technical aspects, basic mathematical notions and elementary machine learning techniques. The second provides an extensive survey of most relevant machine learning tec..
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