fMRI analysis via one-class machine learning techniques

David R. Hardoon; Larry M. Manevitz

fMRI analysis via one-class machine learning techniques

David R. Hardoon
, Larry M. Manevitz

Department of Computer Science

Research output: Contribution to journal › Conference article › peer-review

Abstract

We show how one-class compression Neural Networks and one-class SVM can be applied to fMRI data to learn the classification of brain activity associated with a specific motor activity. For comparison purposes, we use two labeled data and see what degree of classification ability is lost compared with the usual two-class SVM.

Original language	English
Pages (from-to)	1604-1605
Number of pages	2
Journal	IJCAI International Joint Conference on Artificial Intelligence
State	Published - 2005
Event	19th International Joint Conference on Artificial Intelligence, IJCAI 2005 - Edinburgh, United Kingdom Duration: 30 Jul 2005 → 5 Aug 2005

ASJC Scopus subject areas

Artificial Intelligence

Cite this

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title = "fMRI analysis via one-class machine learning techniques",

abstract = "We show how one-class compression Neural Networks and one-class SVM can be applied to fMRI data to learn the classification of brain activity associated with a specific motor activity. For comparison purposes, we use two labeled data and see what degree of classification ability is lost compared with the usual two-class SVM.",

author = "Hardoon, \{David R.\} and Manevitz, \{Larry M.\}",

year = "2005",

language = "English",

pages = "1604--1605",

journal = "IJCAI International Joint Conference on Artificial Intelligence",

issn = "1045-0823",

publisher = "International Joint Conferences on Artificial Intelligence",

note = "19th International Joint Conference on Artificial Intelligence, IJCAI 2005 ; Conference date: 30-07-2005 Through 05-08-2005",

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TY - JOUR

T1 - fMRI analysis via one-class machine learning techniques

AU - Hardoon, David R.

AU - Manevitz, Larry M.

PY - 2005

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N2 - We show how one-class compression Neural Networks and one-class SVM can be applied to fMRI data to learn the classification of brain activity associated with a specific motor activity. For comparison purposes, we use two labeled data and see what degree of classification ability is lost compared with the usual two-class SVM.

AB - We show how one-class compression Neural Networks and one-class SVM can be applied to fMRI data to learn the classification of brain activity associated with a specific motor activity. For comparison purposes, we use two labeled data and see what degree of classification ability is lost compared with the usual two-class SVM.

UR - https://www.scopus.com/pages/publications/33745915605

M3 - Conference article

AN - SCOPUS:33745915605

SN - 1045-0823

SP - 1604

EP - 1605

JO - IJCAI International Joint Conference on Artificial Intelligence

JF - IJCAI International Joint Conference on Artificial Intelligence

T2 - 19th International Joint Conference on Artificial Intelligence, IJCAI 2005

Y2 - 30 July 2005 through 5 August 2005

ER -

fMRI analysis via one-class machine learning techniques

Abstract

ASJC Scopus subject areas

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