| SIPNet & SAHI: Multiscale Sunspot Extraction for High-Resolution Full Solar Images | |
Fan, Dongxin1; Yang, Yunfei1; Feng, Song1; Dai, Wei1; Liang, Bo1; Xiong JP(熊建萍)2
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| 发表期刊 | APPLIED SCIENCES-BASEL
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| 2024-01 | |
| 卷号 | 14期号:1 |
| DOI | 10.3390/app14010007 |
| 产权排序 | 第2完成单位 |
| 收录类别 | SCI |
| 关键词 | sunspots multiscale ultra-small SIPNet |
| 摘要 | Photospheric magnetic fields are manifested as sunspots, which cover various sizes over high-resolution, full-disk, solar continuum images. This paper proposes a novel deep learning method named SIPNet, which is designed to extract and segment multiscale sunspots. It presents a new Switchable Atrous Spatial Pyramid Pooling (SASPP) module based on ASPP, employs an IoU-aware dense object detector, and incorporates a prototype mask generation technique. Furthermore, an open-source framework known as Slicing Aided Hyper Inference (SAHI) is integrated on top of the trained SIPNet model. A comprehensive sunspot dataset is built, containing more than 27,000 sunspots. The precision, recall, and average precision metrics of the SIPNet & SAHI method were measured as 95.7%, 90.2%, and 96.1%, respectively. The results indicate that the SIPNet & SAHI method has good performance in detecting and segmenting large-scale sunspots, particularly in small and ultra-small sunspots. The method also provides a new solution for solving similar problems. |
| 资助项目 | National Natural Science Foundation of China |
| 项目资助者 | National Natural Science Foundation of China |
| 语种 | 英语 |
| 学科领域 | 天文学 |
| 文章类型 | Article |
| 出版者 | MDPI |
| 出版地 | ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND |
| URL | 查看原文 |
| WOS记录号 | WOS:001139247500001 |
| WOS研究方向 | Chemistry ; Engineering ; Materials Science ; Physics |
| WOS类目 | Chemistry, Multidisciplinary ; Engineering, Multidisciplinary ; Materials Science, Multidisciplinary ; Physics, Applied |
| 关键词[WOS] | AREAS |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 版本 | 出版稿 |
| 条目标识符 | http://ir.ynao.ac.cn/handle/114a53/26441 |
| 专题 | 大样本恒星演化研究组 |
| 作者单位 | 1.Faculty of Information Engineering and Automation, Yunnan Key Laboratory of Computer Technology Application, Kunming University of Science and Technology, Kunming 650500, China; 2.Yunnan Astronomical Observatories, Kunming 650051, China |
| 推荐引用方式 GB/T 7714 | Fan, Dongxin,Yang, Yunfei,Feng, Song,et al. SIPNet & SAHI: Multiscale Sunspot Extraction for High-Resolution Full Solar Images[J]. APPLIED SCIENCES-BASEL,2024,14(1). |
| APA | Fan, Dongxin,Yang, Yunfei,Feng, Song,Dai, Wei,Liang, Bo,&熊建萍.(2024).SIPNet & SAHI: Multiscale Sunspot Extraction for High-Resolution Full Solar Images.APPLIED SCIENCES-BASEL,14(1). |
| MLA | Fan, Dongxin,et al."SIPNet & SAHI: Multiscale Sunspot Extraction for High-Resolution Full Solar Images".APPLIED SCIENCES-BASEL 14.1(2024). |
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| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| SIPNet & SAHI_ Multi（22358KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | 浏览 请求全文 | |
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