[HTML][HTML] Convolutional neural network-driven improvements in global cloud detection for landsat 8 and transfer learning on sentinel-2 imagery

S Pang, L Sun, Y Tian, Y Ma, J Wei - Remote Sensing, 2023 - mdpi.com
A stable and reliable cloud detection algorithm is an important step of optical satellite data
preprocessing. Existing threshold methods are mostly based on classifying spectral features …

Leveraging physical rules for weakly supervised cloud detection in remote sensing images

Y Liu, Q Li, X Li, S He, F Liang, Z Yao… - … on Geoscience and …, 2023 - ieeexplore.ieee.org
Cloud detection plays a significant role in remote sensing (RS) image applications. Existing
deep learning-based cloud detection methods rely on massive precise pixelwise …

CLDiff: Weakly Supervised Cloud Detection with Denoising Diffusion Probabilistic Models

Y Liu, Q Li, Z Yao, J Jiang, Z Qiu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Cloud detection is an essential step in remote sensing (RS) image processing, contributing
to various applications. However, existing fully supervised cloud detection methods rely on …

Sensor Independent Cloud and Shadow Masking with Partial Labels and Multimodal Inputs

A Francis - IEEE Transactions on Geoscience and Remote …, 2024 - ieeexplore.ieee.org
A paradigm shift is underway in Earth observation, as deep learning (DL) replaces other
methods for many predictive tasks. Nevertheless, most DL classification models for Earth …

Residual U-Net with Attention for Detecting Clouds in Satellite Imagery

AL De Souza, P Shokri - 2023 - eartharxiv.org
Semantic segmentation of clouds in Earth observation imagery is an important task in a
variety of remote sensing contexts: from the application of atmospheric corrections to being …