A robust morphological classification of high-redshift galaxies using support vector machines on seeing limited images

被引：0

作者：

Huertas-Company, M. ^{[1
,3
]}

Tasca, L. ^{[2
]}

Rouan, D. ^{[1
]}

Pelat, D. ^{[4
]}

Kneib, J.P. ^{[2
]}

Le Fèvre, O. ^{[2
]}

Capak, P. ^{[7
,8
]}

Kartaltepe, J. ^{[9
]}

Koekemoer, A. ^{[11
]}

McCracken, H.J. ^{[5
]}

Salvato, M. ^{[6
,7
]}

Sanders, D.B. ^{[9
]}

Willott, C. ^{[10
]}

机构：

[1] LESIA-Paris Observatory, 5 place Jules Janssen, 92195 Meudon, France

[2] LAM, CNRS, Université de Provence, 38 rue Frédric Joliot-Curie, 13388 Marseille Cedex 13, France

[3] IAA-C/ Camino Bajo de Huétor, 50 - 18008 Granada, Spain

[4] LUTH-Paris Observatory, 5 place Jules Janssen, 92195 Meudon, France

[5] IAP, CNRS, Université Pierre et Marie Curie, 98 boulevard Arago, 75014 Paris, France

[6] Caltech, Pasadena, CA 91125, United States

[7] 105-24 Caltech, Pasadena, CA 91125, United States

[8] Spitzer Science Center, 314-6 Caltech, Pasadena, CA 91125, United States

[9] Institute for Astronomy, University of Hawaii, 2680 Woodlawn Drive, Honolulu, HI 96822, United States

[10] Physics Department, University of Ottawa, MacDonald Hall, 150 Louis Pasteur, Ottawa, ON K1N 6N5, Canada

[11] Space Telescope Science Institute, 3700 San Martin Drive, Baltimore MD 21218, United States

来源：

Astronomy and Astrophysics | 2009年 / 497卷 / 03期

关键词：

Galaxies;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Journal article (JA)

引用

下载

页码：743 / 753

共 50 条

[31] Efficient and Robust Classification of Seismic Data using Nonlinear Support Vector Machines
Hickmann, Kyle S.
Hyman, Jeffrey
Srinivasan, Gowri
2017 FIFTY-FIRST ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS, 2017, : 148 - 155
[32] Classification of epileptic cerebral activity using robust features and Support Vector Machines
Mahjoub, Chahira
Chaibi, Sahbi
Lajnef, Tarek
Kachouri, Abdennaceur
2016 SECOND INTERNATIONAL IMAGE PROCESSING, APPLICATIONS AND SYSTEMS (IPAS), 2016,
[33] Classification of apple images using support vector machines and deep residual networks
Sevim Adige
Rifat Kurban
Ali Durmuş
Ercan Karaköse
Neural Computing and Applications, 2023, 35 : 12073 - 12087
[34] Classification of damages in composite images using Zernike moments and support vector machines
Fredo, A. R. Jac
Abilash, R. S.
Femi, R.
Mythili, A.
Kumar, C. Suresh
COMPOSITES PART B-ENGINEERING, 2019, 168 : 77 - 86
[35] Classification of apple images using support vector machines and deep residual networks
Adige, Sevim
Kurban, Rifat
Durmus, Ali
Karakose, Ercan
NEURAL COMPUTING & APPLICATIONS, 2023, 35 (16): : 12073 - 12087
[36] Classification of iPSC Colony Images Using Hierarchical Strategies with Support Vector Machines
Joutsijoki, Henry
Rasku, Jyrki
Haponen, Markus
Baldin, Ivan
Gizatdinova, Yulia
Paci, Michelangelo
Saarikoski, Jyri
Varpa, Kirsi
Siirtola, Harri
Avalos-Salguero, Jorge
Iltanen, Kati
Laurikkala, Jorma
Penttinen, Kirsi
Hyttinen, Jari
Aalto-Setala, Katriina
Juhola, Martti
2014 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DATA MINING (CIDM), 2014, : 86 - 92
[37] Lung Nodule Classification in CT Thorax Images using Support Vector Machines
Madero Orozco, Hiram
Vergara Villegas, Osslan Osiris
Ochoa Dominguez, Humberto de Jesus
Cruz Sanchez, Vianey Guadalupe
2013 12TH MEXICAN INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE (MICAI 2013), 2013, : 277 - 283
[38] Robust γ-filter using support vector machines
Camps-Valls, G
Martínez-Ramón, M
Rojo-Alvarez, JL
Soria-Olivas, E
NEUROCOMPUTING, 2004, 62 : 493 - 499
[39] Robust ASR using support vector machines
Solera-Urena, R.
Martin-Iglesias, D.
Gallardo-Antolin, A.
Pelaez-Moreno, C.
Diaz-de-Maria, F.
SPEECH COMMUNICATION, 2007, 49 (04) : 253 - 267
[40] Segmentation of images using support vector machines
Chen, QY
Yang, Q
PROCEEDINGS OF THE 2004 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2004, : 3304 - 3306

← 1 2 3 4 5 →