A deep learning approach for detecting candidates of supernova remnants
文献类型：期刊论文
| 作者 | Liu, Wei2; Mu, Meng2; Dai, Cong2; Wang, Bing-Yi2; Wu, Kang2; Yu, Xian-Chuan2; Tian, Wen-Wu3; Zhang, Meng-Fei3; Wang, Hong-Feng1 |
| 刊名 | RESEARCH IN ASTRONOMY AND ASTROPHYSICS
 |
| 出版日期 | 2019-03-01 |
| 卷号 | 19期号:3页码:12 |
| 关键词 | methods: data analysis techniques: image processing stars: fundamental parameters |
| ISSN号 | 1674-4527 |
| DOI | 10.1088/1674-4527/19/3/42 |
| 英文摘要 | Detecting supernova remnant (SNR) candidates in the interstellar medium is a challenging task because SNRs have weak radio signals and irregular shapes. The use of a convolutional neural network is a deep learning method that can help us extract various features from images. To extract SNRs from astronomical images and estimate the positions of SNR candidates, we design the SNR-Net model composed of a training component and a detection component. In addition, transfer learning is used to initialize the network parameters, which improves the speed and accuracy of network training. We apply a T-T plot (of the different brightness temperatures of map pixels at two different frequencies) to calculate the spectral index of SNR candidates. To accelerate the scientific computing process, we take advantage of innovative hardware architecture, such as deep learning optimized graphics processing units, which increases the speed of computation by a factor of 5. A case study suggests that SNR-Net may be applicable to detecting extended sources in the images automatically. |
| WOS关键词 | RADIO SPECTRAL INDEX ; NOVA REMNANTS ; REGIONS |
| 资助项目 | National Natural Science Foundation of China[41272359] ; Ministry of Land and Resources for the Public Welfare Industry Research Projects[201511079-02] ; Natural Science Foundation of Shandong[ZR2015FL006] |
| WOS研究方向 | Astronomy & Astrophysics |
| 语种 | 英语 |
| WOS记录号 | WOS:000462485200012 |
| 出版者 | NATL ASTRONOMICAL OBSERVATORIES, CHIN ACAD SCIENCES |
| 资助机构 | National Natural Science Foundation of China ; National Natural Science Foundation of China ; Ministry of Land and Resources for the Public Welfare Industry Research Projects ; Ministry of Land and Resources for the Public Welfare Industry Research Projects ; Natural Science Foundation of Shandong ; Natural Science Foundation of Shandong ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Ministry of Land and Resources for the Public Welfare Industry Research Projects ; Ministry of Land and Resources for the Public Welfare Industry Research Projects ; Natural Science Foundation of Shandong ; Natural Science Foundation of Shandong ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Ministry of Land and Resources for the Public Welfare Industry Research Projects ; Ministry of Land and Resources for the Public Welfare Industry Research Projects ; Natural Science Foundation of Shandong ; Natural Science Foundation of Shandong ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Ministry of Land and Resources for the Public Welfare Industry Research Projects ; Ministry of Land and Resources for the Public Welfare Industry Research Projects ; Natural Science Foundation of Shandong ; Natural Science Foundation of Shandong |
| 源URL | [http://ir.bao.ac.cn/handle/114a11/25714]  |
| 专题 | 中国科学院国家天文台 |
| 通讯作者 | Liu, Wei |
| 作者单位 | 1.Dezhou Univ, Sch Informat Management, Dezhou 253023, Peoples R China 2.Beijing Normal Univ, Coll Informat Sci & Technol, Beijing 100875, Peoples R China 3.Chinese Acad Sci, Natl Astron Observ, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Wei,Mu, Meng,Dai, Cong,et al. A deep learning approach for detecting candidates of supernova remnants[J]. RESEARCH IN ASTRONOMY AND ASTROPHYSICS,2019,19(3):12. |
| APA | Liu, Wei.,Mu, Meng.,Dai, Cong.,Wang, Bing-Yi.,Wu, Kang.,...&Wang, Hong-Feng.(2019).A deep learning approach for detecting candidates of supernova remnants.RESEARCH IN ASTRONOMY AND ASTROPHYSICS,19(3),12. |
| MLA | Liu, Wei,et al."A deep learning approach for detecting candidates of supernova remnants".RESEARCH IN ASTRONOMY AND ASTROPHYSICS 19.3(2019):12. |
入库方式： OAI收割
来源：国家天文台
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