论文标题
免费注释的数据，用于显微镜中的深度学习？搭便车指南
Free annotated data for deep learning in microscopy? A hitchhiker's guide
论文作者
论文摘要
在显微镜检查中，许多深度学习模型作为先决条件的获取和注释大型数据集的时间负担和成本通常使这些方法变得不切实际。可以放松注释数据的要求吗？是否可以从其他应用程序字段中从数据集收集的知识借用并利用它进行显微镜？在这里，我们旨在概述最近出现在生物微观镜检查中成功培训基于学习的方法的方法。
In microscopy, the time burden and cost of acquiring and annotating large datasets that many deep learning models take as a prerequisite, often appears to make these methods impractical. Can this requirement for annotated data be relaxed? Is it possible to borrow the knowledge gathered from datasets in other application fields and leverage it for microscopy? Here, we aim to provide an overview of methods that have recently emerged to successfully train learning-based methods in bio-microscopy.
