Investigation of kernel-based machine learning techniques for infrasound signal classification

Publikation: KonferencebidragPosterForskning

Standard

Investigation of kernel-based machine learning techniques for infrasound signal classification. / Tuma, Matthias; Igel, Christian.

2013. Poster session præsenteret ved CTBTO Science and Technology 2013 Conference, Wien, Østrig.

Publikation: KonferencebidragPosterForskning

Harvard

Tuma, M & Igel, C 2013, 'Investigation of kernel-based machine learning techniques for infrasound signal classification', CTBTO Science and Technology 2013 Conference, Wien, Østrig, 17/06/2013 - 21/06/2013. <http://www.ctbto.org/fileadmin/snt2013/posters/T3-P67.pdf>

APA

Tuma, M., & Igel, C. (2013). Investigation of kernel-based machine learning techniques for infrasound signal classification. Poster session præsenteret ved CTBTO Science and Technology 2013 Conference, Wien, Østrig. http://www.ctbto.org/fileadmin/snt2013/posters/T3-P67.pdf

Vancouver

Tuma M, Igel C. Investigation of kernel-based machine learning techniques for infrasound signal classification. 2013. Poster session præsenteret ved CTBTO Science and Technology 2013 Conference, Wien, Østrig.

Author

Tuma, Matthias ; Igel, Christian. / Investigation of kernel-based machine learning techniques for infrasound signal classification. Poster session præsenteret ved CTBTO Science and Technology 2013 Conference, Wien, Østrig.1 s.

Bibtex

@conference{e3523d5e05744325804c0f7e8c8c0c0a,
title = "Investigation of kernel-based machine learning techniques for infrasound signal classification",
author = "Matthias Tuma and Christian Igel",
year = "2013",
language = "English",
note = "CTBTO Science and Technology 2013 Conference, SnT2013 ; Conference date: 17-06-2013 Through 21-06-2013",

}

RIS

TY - CONF

T1 - Investigation of kernel-based machine learning techniques for infrasound signal classification

AU - Tuma, Matthias

AU - Igel, Christian

PY - 2013

Y1 - 2013

M3 - Poster

T2 - CTBTO Science and Technology 2013 Conference

Y2 - 17 June 2013 through 21 June 2013

ER -

ID: 168603054