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M4Fog: A Global Multi-Regional, Multi-Modal, and Multi-Stage Dataset for Marine Fog Detection and Forecasting to Bridge Ocean and Atmosphere
This is the code and data for M4Fog: A Global Multi-Regional, Multi-Modal, and Multi-Stage Dataset for Marine Fog Detection and …
PDF 引用 代码 Track-A H8/9 Track-A FY4A Track-A GOES Track-B H8/9 Track-C H8/9 Area1 Track-C H8/9 Multi-areas Track-C FY4A Track-C Meteo-multiareas Track-C Meteo-single-area ICOADS
M4Fog: A Global Multi-Regional, Multi-Modal, and Multi-Stage Dataset for Marine Fog Detection and Forecasting to Bridge Ocean and Atmosphere
MoANet: A Motion Attention Network for Sea Fog Detection in Time Series Meteorological Satellite Imagery
Sea fog detection is a significant and challenging issue in meteorological satellite imagery. Distinguishing between sea fog and low …
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MoANet: A Motion Attention Network for Sea Fog Detection in Time Series Meteorological Satellite Imagery
Weakly Supervised Sea Fog Detection in Remote Sensing Images via Prototype Learning
Sea fog detection is a challenging and significant task in the field of remote sensing. Deep learning-based methods have shown …
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Weakly Supervised Sea Fog Detection in Remote Sensing Images via Prototype Learning
SeaMAE: Masked Pre-Training with Meteorological Satellite Imagery for Sea Fog Detection
Sea fog detection (SFD) presents a significant challenge in the field of intelligent Earth observation, particularly in analyzing …
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SeaMAE: Masked Pre-Training with Meteorological Satellite Imagery for Sea Fog Detection
Weather2K: A Multivariate Spatio-Temporal Benchmark Dataset for Meteorological Forecasting Based on Real-Time Observation Data from Ground Weather Stations
Weather forecasting is one of the cornerstones of meteorological work. In this paper, we present a new benchmark dataset named …
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Weather2K: A Multivariate Spatio-Temporal Benchmark Dataset for Meteorological Forecasting Based on Real-Time Observation Data from Ground Weather Stations
Attention based Long Short-Term Memory Network for Coastal Visibility Forecast
Visibility prediction in coastal areas has always been an important issue affecting the safety of residents and the efficiency of urban …
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Identify, Guess and Reconstruct- Three Principles for Cloud Removal Task
Remote sensing images serve a significant role in earth observation to tackle climate change and post-disaster reconstruction concerns. …
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Identify, Guess and Reconstruct- Three Principles for Cloud Removal Task
Annotating Only at Definite Pixels- A Novel Weakly Supervised Semantic Segmentation Method for Sea Fog Recognition
Sea fog recognition is a challenging and significant semantic segmentation task in remote sensing images. The fully supervised learning …
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Annotating Only at Definite Pixels- A Novel Weakly Supervised Semantic Segmentation Method for Sea Fog Recognition
The Eyes of the Gods: A Survey of Unsupervised Domain Adaptation Methods Based on Remote Sensing Data
With the rapid development of the remote sensing monitoring and computer vision technology, the deep learning method has made a great …
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Domain Adaptation on Multiple Cloud Recognition From Different Types of Meteorological Satellite
Meteorological satellites have become an indispensable meteorological tool for earth observation, as aiding in areas such as cloud …
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Domain Adaptation on Multiple Cloud Recognition From Different Types of Meteorological Satellite
Sea fog detection based on unsupervised domain adaptation
Sea fog detection with remote sensing images is a challenging task. Driven by the different image characteristics between fog and other …
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Sea fog detection based on unsupervised domain adaptation
Sea Fog Monitoring Method Based on Deep Learning Satellite Multi-channel Image Fusion
Sea fog, whether on the sea or the coast, has adverse effects on transportation, marine fishing, marine development projects, and …
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Sea Fog Monitoring Method Based on Deep Learning Satellite Multi-channel Image Fusion
A Correlation Context-Driven Method for Sea Fog Detection in Meteorological Satellite Imagery
Sea fog detection is a challenging and essential issue in satellite remote sensing. Although conventional threshold methods and deep …
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A Correlation Context-Driven Method for Sea Fog Detection in Meteorological Satellite Imagery