科斯米卡:用于天文物体检测的新型数据集,可在多种检测架构之间进行评估
Evgenii Piratinskii1, Irina Rabaev1
1Software Engineering Department, Shamoon College of Engineering, 56 Bialik St., Be'er Sheva 8410802, Israel.
Journal of imaging
|June 25, 2025
概括
我们介绍COSMICA,这是一个用于在天文图像中检测天体的新数据集. YOLOv11显示了对彗星,星系和星云实时检测的最佳性能.
科学领域:
- 天文学和天体物理学
- 计算机科学 计算机科学
- 人工智能的人工智能
背景情况:
- 在天文图像中准确检测天体是非常重要的,但由于噪音和物体特征的变化而具有挑战性.
- 传统方法在实时应用和复杂的观测条件下往往不足.
研究的目的:
- 介绍COSMICA,这是一个精心策划的数据集,来自业余观测的手动注释天文图像.
- 评估现代物体检测模型的性能,以实时识别天文物体.
主要方法:
- 在COSMICA数据集上调查了YOLOv8,YOLOv9,YOLOv11,EfficientDet-Lite0和MobileNetV3-FasterRCNN-FPN. 在COSMICA数据集上进行了调查.
- 在一致的实验条件下使用mAP,精度,回忆和推断速度等指标评估模型.
主要成果:
- 在测试的模型中,YOLOv11实现了最高的整体精度和计算效率.
- 所有评估的模型都在探测彗星,星系,星云和球状星团方面表现出不同程度的成功.
结论:
- 深度学习模型,特别是YOLOv11,在观测天文学中显示了实时天体检测的重大前景.
- 像COSMICA这样的特定领域数据集对于训练用于天文学应用的强大的AI模型至关重要.
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