点建议网络:通过深学习加速点源源的发现 (Point Proposal Network: Accelerating Point Source Detection Through Deep Learning)

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Point source detection techniques are used to identify and localise point sources in radio astronomical surveys. With the development of the Square Kilometre Array (SKA) telescope, survey images will see a massive increase in size from Gigapixels to Terapixels. Point source detection has already proven to be a challenge in recent surveys performed by SKA pathfinder telescopes. This paper proposes the Point Proposal Network (PPN): a point source detector that utilises deep convolutional neural networks for fast source detection. Results measured on simulated MeerKAT images show that, although less precise when compared to leading alternative approaches, PPN performs source detection faster and is able to scale to large images, unlike the alternative approaches.

翻译：利用点源探测技术在射电天文测量中查明和定位点源。随着Squa Komilm Array(SKA)望远镜的开发,调查图像将看到从Gigapixels到Terapixels的体积大幅上升。点源探测已经证明是SKA路透望远镜最近进行的调查中的一项挑战。本文提议了点建议网络(PPPN):一个点源检测器,它利用深电弧神经网络进行快速源探测。模拟MeerKAT图像测量的结果显示,PPN的源探测速度较快,而且能够向大图像放大,而不同于其他方法。