Cloud masking is a crucial task that is well-motivated for meteorology and its applications in environmental and atmospheric sciences. Its goal is, given satellite images, to accurately generate cloud masks that identify each pixel in image to contain either cloud or clear sky. In this paper, we summarize some of the ongoing research activities in cloud masking, with a focus on the research and benchmark currently conducted in MLCommons Science Working Group. This overview is produced with the hope that others will have an easier time getting started and collaborate on the activities related to MLCommons Cloud Mask Benchmark.

翻译：云掩膜是一项对气象学及其在环境和大气科学中的应用具有重要推动意义的关键任务。其目标是：给定卫星图像，准确生成云掩膜，识别图像中每个像素是包含云层还是晴空。本文总结了当前云掩膜领域的一些研究进展，重点介绍了MLCommons科学工作组正在开展的研究与基准测试工作。本概述旨在为相关研究者提供便捷的入门指引，并促进围绕MLCommons云掩膜基准开展合作。