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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
- 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
- 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
- Attention based Long Short-Term Memory Network for Coastal Visibility Forecast
- Annotating Only at Definite Pixels- A Novel Weakly Supervised Semantic Segmentation Method for Sea Fog Recognition
- Identify, Guess and Reconstruct- Three Principles for Cloud Removal Task
- The Eyes of the Gods: A Survey of Unsupervised Domain Adaptation Methods Based on Remote Sensing Data
- Domain Adaptation on Multiple Cloud Recognition From Different Types of Meteorological Satellite
- Sea fog detection based on unsupervised domain adaptation
- Sea Fog Monitoring Method Based on Deep Learning Satellite Multi-channel Image Fusion
- 基于无监督域适应的不同类型气象卫星的多云识别系统
- 一种基于机器学习算法的有监督假彩色图像合成方法
- A Correlation Context-Driven Method for Sea Fog Detection in Meteorological Satellite Imagery
- 基于静止气象卫星影像序列的云雾自动判识方法及系统
- 一种基于气象卫星图像和深度迁移学习的海雾识别方法
- 一种基于深度学习和卫星遥感技术的海雾检测方法
- 一种基于卫星图像的空气污染估计方法