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Published in 2018 at "Asia-Pacific Journal of Atmospheric Sciences"
DOI: 10.1007/s13143-018-0050-y
Abstract: This paper presents a nighttime sea fog detection algorithm incorporating unsupervised learning technique. The algorithm is based on data sets that combine brightness temperatures from the 3.7 μm and 10.8 μm channels of the meteorological imager (MI)…
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Keywords:
sea;
nighttime sea;
unsupervised learning;
fog detection ... See more keywords
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Published in 2021 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2020.3036815
Abstract: Fog is a hazardous weather event that can endanger navigation, aviation, and transportation. While human has several limitations in detecting and forecasting offshore fog, satellite remote sensing offers cost-effective images. In this study, a probability-based…
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Keywords:
fog;
fog detection;
sea fog;
probability ... See more keywords
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Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2021.3095731
Abstract: Sea fog detection is a challenging and essential issue in satellite remote sensing. Although conventional threshold methods and deep learning methods can achieve pixel-level classification, it is difficult to distinguish ambiguous boundaries and thin structures…
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Keywords:
fog detection;
sea fog;
context driven;
correlation context ... See more keywords
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Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3196177
Abstract: Sea fog significantly threatens the safety of maritime activities. This article develops a sea fog detection dataset (SFDD) and a dual-branch sea fog detection network (DB-SFNet). We investigate all the observed sea fog events in…
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Keywords:
fog detection;
sea fog;
dual branch;
sea ... See more keywords