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Searching for previously unknown classes of objects in the AKARI-NEP Deep data with fuzzy logic SVM algorithm
https://jaxa.repo.nii.ac.jp/records/3150
https://jaxa.repo.nii.ac.jp/records/3150d381f5b2-bad8-4b77-8dce-6a73f3329155
名前 / ファイル | ライセンス | アクション |
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AA1730026076.pdf (668.4 kB)
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Item type | 会議発表論文 / Conference Paper(1) | |||||
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公開日 | 2018-05-18 | |||||
タイトル | ||||||
言語 | en | |||||
タイトル | Searching for previously unknown classes of objects in the AKARI-NEP Deep data with fuzzy logic SVM algorithm | |||||
言語 | ||||||
言語 | eng | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | automatic classification | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | machine learning | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | galaxy evolution | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_5794 | |||||
資源タイプ | conference paper | |||||
著者 |
Poliszczuk, Artem
× Poliszczuk, Artem× Solarz, Aleksandra× Pollo, Agnieszka× The NEP-Deep Team |
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著者所属(英) | ||||||
en | ||||||
National Center for Nuclear Research, Poland | ||||||
著者所属(英) | ||||||
en | ||||||
National Center for Nuclear Research, Poland | ||||||
著者所属(英) | ||||||
en | ||||||
National Center for Nuclear Research, Poland : Astronomical Observatory of the Jagiellonian University | ||||||
出版者 | ||||||
出版者 | 宇宙航空研究開発機構(JAXA) | |||||
出版者(英) | ||||||
出版者 | Japan Aerospace Exploration Agency (JAXA) | |||||
書誌情報 |
宇宙航空研究開発機構特別資料 en : JAXA Special Publication: The Cosmic Wheel and the Legacy of the AKARI archive: from galaxies and stars to planets and life 巻 JAXA-SP-17-009E, p. 375-378, 発行日 2018-03-09 |
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会議概要(会議名, 開催地, 会期, 主催者等) | ||||||
内容記述タイプ | Other | |||||
内容記述 | 第4回「あかり」国際会議 (2017年10月17-20日. 東京大学), 文京区, 東京 | |||||
会議概要(会議名, 開催地, 会期, 主催者等)(英) | ||||||
内容記述タイプ | Other | |||||
内容記述 | The 4th AKARI International Conference: The Cosmic Wheel and the Legacy of the AKARI archive: from galaxies and stars to planets and life (October 17-20, 2017. The University of Tokyo), Bunkyo-ku, Tokyo, Japan | |||||
抄録(英) | ||||||
内容記述タイプ | Other | |||||
内容記述 | In this proceedings application of a fuzzy Support Vector Machine (FSVM) learning algorithm, to classify mid-infrared (MIR) sources from the AKARI NEP Deep field into three classes: stars, galaxies and AGNs, is presented. FSVM is an improved version of the classical SVM algorithm, incorporating measurement errors into the classification process; this is the first successful application of this algorithm in the astronomy. We created reliable catalogues of galaxies, stars and AGNs consisting of objects with MIR measurements, some of them with no optical counterparts. Some examples of identified objects are shown, among them O-rich and C-rich AGB stars. | |||||
内容記述 | ||||||
内容記述タイプ | Other | |||||
内容記述 | 形態: カラー図版あり | |||||
内容記述(英) | ||||||
内容記述タイプ | Other | |||||
内容記述 | Physical characteristics: Original contains color illustrations | |||||
ISSNONLINE | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 2433-2232 | |||||
資料番号 | ||||||
内容記述タイプ | Other | |||||
内容記述 | 資料番号: AA1730026076 | |||||
レポート番号 | ||||||
内容記述タイプ | Other | |||||
内容記述 | レポート番号: JAXA-SP-17-009E |