ĀLOKA - 快速有效的光学暂现源识别框架
Peng Jia
这个是A Rapid and Efficient Optical Transients Identification Framework based on Multimodal Neural Network and Machine Learning Operations论文的Docker版本代码，代码可以直接部署于linux系统，用于从0构建光学暂现源检测、分析、后随验证和MLOps服务的代码。
文件
atif_v1.tar
44.18 GB
论文信息
论文标题:
A Rapid and Efficient Optical Transients Identification Framework based on Multimodal Neural Network and Machine Learning Operations
发表期刊:
ApJs
标识符
CSTR:
11379.11.101641
DOI:
10.12149/101641
VO Identifier:
ivo://China-VO/paperdata/101641
发布时间:
2025-08-01
使用统计
总下载量
190
引用
Peng Jia et al. 2025. ĀLOKA - A Rapid and Efficient Optical Transients Identification Framework. 版本 1.0. https://doi.org/10.12149/101641
@misc{10.12149/101641,
doi = {10.12149/101641},
url = {https://doi.org/10.12149/101641},
author = {Peng Jia},
title = {ĀLOKA - A Rapid and Efficient Optical Transients Identification Framework },
version = {1.0},
publisher = {Nataional Astronomical Data Center of China},
year= {2025}
}
doi = {10.12149/101641},
url = {https://doi.org/10.12149/101641},
author = {Peng Jia},
title = {ĀLOKA - A Rapid and Efficient Optical Transients Identification Framework },
version = {1.0},
publisher = {Nataional Astronomical Data Center of China},
year= {2025}
}
版本