File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1086/420967
- Scopus: eid_2-s2.0-3142770461
- WOS: WOS:000221605200003
- Find via
Supplementary
- Citations:
- Appears in Collections:
Article: Automated classification of 2000 bright iras sources
Title | Automated classification of 2000 bright iras sources |
---|---|
Authors | |
Keywords | Infrared: Galaxies Methods: Data Analysis |
Issue Date | 2004 |
Citation | Astrophysical Journal, Supplement Series, 2004, v. 152 n. 2, p. 201-209 How to Cite? |
Abstract | An artificial neural network (ANN) scheme has been employed that uses a supervised back-propagation algorithm to classify 2000 bright sources from the Calgary database of Infrared Astronomical Satellite (IRAS) spectra in the region 8-23 μm. The database has been classified into 17 predefined classes based on the spectral morphology. We have been able to classify over 80% of the sources correctly in the first instance. The speed and robustness of the scheme will allow us to classify the whole of the Low Resolution Spectrometer database, containing more than 50,000 sources, in the near future. |
Persistent Identifier | http://hdl.handle.net/10722/179693 |
ISSN | 2023 Impact Factor: 8.6 2023 SCImago Journal Rankings: 3.329 |
ISI Accession Number ID | |
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Gupta, R | en_US |
dc.contributor.author | Singh, HP | en_US |
dc.contributor.author | Volk, K | en_US |
dc.contributor.author | Kwok, S | en_US |
dc.date.accessioned | 2012-12-19T10:02:52Z | - |
dc.date.available | 2012-12-19T10:02:52Z | - |
dc.date.issued | 2004 | en_US |
dc.identifier.citation | Astrophysical Journal, Supplement Series, 2004, v. 152 n. 2, p. 201-209 | en_US |
dc.identifier.issn | 0067-0049 | en_US |
dc.identifier.uri | http://hdl.handle.net/10722/179693 | - |
dc.description.abstract | An artificial neural network (ANN) scheme has been employed that uses a supervised back-propagation algorithm to classify 2000 bright sources from the Calgary database of Infrared Astronomical Satellite (IRAS) spectra in the region 8-23 μm. The database has been classified into 17 predefined classes based on the spectral morphology. We have been able to classify over 80% of the sources correctly in the first instance. The speed and robustness of the scheme will allow us to classify the whole of the Low Resolution Spectrometer database, containing more than 50,000 sources, in the near future. | en_US |
dc.language | eng | en_US |
dc.relation.ispartof | Astrophysical Journal, Supplement Series | en_US |
dc.subject | Infrared: Galaxies | en_US |
dc.subject | Methods: Data Analysis | en_US |
dc.title | Automated classification of 2000 bright iras sources | en_US |
dc.type | Article | en_US |
dc.identifier.email | Kwok, S: deannote@hku.hk | en_US |
dc.identifier.authority | Kwok, S=rp00716 | en_US |
dc.description.nature | link_to_subscribed_fulltext | en_US |
dc.identifier.doi | 10.1086/420967 | en_US |
dc.identifier.scopus | eid_2-s2.0-3142770461 | en_US |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-3142770461&selection=ref&src=s&origin=recordpage | en_US |
dc.identifier.volume | 152 | en_US |
dc.identifier.issue | 2 | en_US |
dc.identifier.spage | 201 | en_US |
dc.identifier.epage | 209 | en_US |
dc.identifier.isi | WOS:000221605200003 | - |
dc.publisher.place | United States | en_US |
dc.identifier.scopusauthorid | Gupta, R=7501320703 | en_US |
dc.identifier.scopusauthorid | Singh, HP=35499554200 | en_US |
dc.identifier.scopusauthorid | Volk, K=7006571965 | en_US |
dc.identifier.scopusauthorid | Kwok, S=22980498300 | en_US |
dc.identifier.issnl | 0067-0049 | - |