NDLI: Support Vector Machine Applications in Terahertz Pulsed Signals Feature Sets

Content Provider	IEEE Xplore Digital Library
Author	Xiaoxia Yin Ng, B.W.-H. Fischer, B.M. Ferguson, B. Abbott, D.
Copyright Year	2001
Abstract	In the past decade, terahertz radiation (T-rays) have been extensively applied within the fields of industrial and biomedical imaging, owing to their noninvasive property. Support vector machine (SVM) learning algorithms are sufficiently powerful to detect patterns hidden inside noisy biomedical measurements. This paper introduces a frequency orientation component method to extract T-ray feature sets for the application of two- and multiclass classification using SVMs. Effective discriminations of ribonucleic acid (RNA) samples and various powdered substances are demonstrated. The development of this method has become important in T-ray chemical sensing and image processing, which results in enhanced detectability useful for many applications, such as quality control, security detection and clinic diagnosis.
Sponsorship	IEEE Sensors Council
Starting Page	1597
Ending Page	1608
Page Count	12
File Size	1357461
File Format	PDF
ISSN	1530437X
Volume Number	7
Issue Number	12
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-12-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Support vector machine classification RNA Biomedical imaging Machine learning Biomedical measurements Frequency Feature extraction Chemical processes Image processing terahertz time- domain spectroscopy Pairwise classification ribonucleic acid (RNA) support vector machines (SVMs) terahertz
Content Type	Text
Resource Type	Article
Subject	Instrumentation Electrical and Electronic Engineering

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Predicting the risk of metabolic acidosis for newborns based on fetal heart rate signal classification using support vector machines

Automated Biosignal Quality Analysis for Electromyography Using a One-Class Support Vector Machine

An Automatic System for the Analysis and Classification of Human Atrial Fibrillation Patterns from Intracardiac Electrograms

Chilean Wine Classification Using Volatile Organic Compounds Data Obtained With a Fast GC Analyzer

Testing Stationarity With Surrogates: A Time-Frequency Approach

Quantitative Determination of Cyfluthrin in N-Hexane by Terahertz Time-Domain Spectroscopy With Chemometrics Methods

Optimized support vector machines for nonstationary signal classification

Comparison of Vector Stacking, Multi-SVMs Fuzzy Output, and Multi-SVMs Voting Methods for Multiscale VHR Urban Mapping

Constructing Accurate Contact Maps for Hydroxyl-Radical-Cleavage-Based High-Throughput RNA Structure Inference

Support Vector Machine Applications in Terahertz Pulsed Signals Feature Sets

Similar Documents

Predicting the risk of metabolic acidosis for newborns based on fetal heart rate signal classification using support vector machines

Automated Biosignal Quality Analysis for Electromyography Using a One-Class Support Vector Machine

An Automatic System for the Analysis and Classification of Human Atrial Fibrillation Patterns from Intracardiac Electrograms

Chilean Wine Classification Using Volatile Organic Compounds Data Obtained With a Fast GC Analyzer

Testing Stationarity With Surrogates: A Time-Frequency Approach

Quantitative Determination of Cyfluthrin in N-Hexane by Terahertz Time-Domain Spectroscopy With Chemometrics Methods

Optimized support vector machines for nonstationary signal classification

Comparison of Vector Stacking, Multi-SVMs Fuzzy Output, and Multi-SVMs Voting Methods for Multiscale VHR Urban Mapping

Constructing Accurate Contact Maps for Hydroxyl-Radical-Cleavage-Based High-Throughput RNA Structure Inference

Support Vector Machine Applications in Terahertz Pulsed Signals Feature Sets