Pattern Recognition Technologies and Applications Recent Advances 1st Edition by Brijesh Verma, Michael Blumenstein – Ebook PDF Instant Download/Delivery: 1599048094, 9781599048093
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Product details:
ISBN 10: 1599048094
ISBN 13: 9781599048093
Author: Brijesh Verma, Michael Blumenstein
The nature of handwriting in our society has significantly altered over the ages due to the introduction of new technologies such as computers and the World Wide Web. With increases in the amount of signature verification needs, state of the art internet and paper-based automated recognition methods are necessary. Pattern Recognition Technologies and Applications: Recent Advances provides cutting-edge pattern recognition techniques and applications. Written by world-renowned experts in their field, this easy to understand book is a must have for those seeking explanation in topics such as on- and offline handwriting and speech recognition, signature verification, and gender classification.
Table of contents:
Chapter I: Fusion of Segmentation Strategies for Off-Line Cursive Handwriting Recognition
Chapter II: Elastic Matching Techniques for Handwritten Character Recognition
Chapter III: State of the Art in Off-Line Signature Verification
Chapter IV: An Automatic Off-Line Signature Verification and Forgery Detection System
Chapter V: Introduction to Speech Recognition
Chapter VI: Seeking Patterns in the Forensic Analysis of Handwriting and Speech
Chapter VII: Image Pattern Recognition- Based Morphological Structure and Applications
Chapter VIII: Robust Face Recognition Technique for a Real-Time Embedded Face Recognition System
Chapter IX: Occlusion Sequence Mining for Activity Discovery from Surveillance Videos
Chapter X: Human Detection in Static Images
Chapter XI: A Brain-Inspired Visual Pattern Recognition Architecture and Its Applications
Chapter XII: Significance of Logic Synthesis in FPGA-Based Design of Image and Signal Processing Sys
Chapter XIII: A Novel Support Vector Machine with Class-Dependent Features for Biomedical Data
Chapter XIV: A Unified Approach to Support Vector Machines
Chapter XV: Cluster Ensemble and Multi- Objective Clustering Methods
Chapter XVI: Implementing Negative Correlation Learning in Evolutionary Ensembles with Suitable Spec
Chapter XVII: A Recurrent Probabilistic Neural Network for EMG Pattern Recognition
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Tags: Brijesh Verma, Michael Blumenstein, Recognition, Applications