An Overview of MLCommons Cloud Mask Benchmark: Related Research and Data

December 08, 2023 ยท The Cartographer ยท ๐Ÿ› arXiv.org

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
Survey/review paper โ€” maps the landscape rather than implementing a method.

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"Title-pattern auto-detect: An Overview of MLCommons Cloud Mask Benchmark: Related Research and Data"

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Authors Gregor von Laszewski, Ruochen Gu arXiv ID 2312.04799 Category cs.DC: Distributed Computing Cross-listed cs.AI Citations 1 Venue arXiv.org Last Checked 4 days ago
Abstract
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.
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