Comprehensive quality assessment of optical satellite imagery using weakly supervised video learning
VJ Pasquarella, CF Brown… - Proceedings of the …, 2023 - openaccess.thecvf.com
Identifying high-quality (ie, relatively clear) measurements of surface conditions is a near-
universal first step in working with optical satellite imagery. Many cloud masking algorithms …
universal first step in working with optical satellite imagery. Many cloud masking algorithms …
A review of cancer data fusion methods based on deep learning
With advancements in modern medical technology, an increasing amount of cancer-related
information can be acquired through various means, such as genomics, proteomics …
information can be acquired through various means, such as genomics, proteomics …
SSGAN: Cloud removal in satellite images using spatiospectral generative adversarial network
Satellite data's reliability, uniformity, and global scanning capabilities have revolutionized
agricultural monitoring and crop management. However, the presence of clouds in satellite …
agricultural monitoring and crop management. However, the presence of clouds in satellite …
MultiRS flood mapper: a google earth engine application for water extent mapping with multimodal remote sensing and quantile-based postprocessing
There is a growing interest in developing GEE applications to improve the reusability of GEE
scripts and reduce manual effort for water-body extraction. Right now, there is a need for …
scripts and reduce manual effort for water-body extraction. Right now, there is a need for …
A critical review on multi-sensor and multi-platform remote sensing data fusion approaches: current status and prospects
F Samadzadegan, A Toosi… - International Journal of …, 2024 - Taylor & Francis
Numerous remote sensing (RS) systems currently collect data about Earth and its
environments. However, each system provides limited data in terms of spatial resolution …
environments. However, each system provides limited data in terms of spatial resolution …
SOSSF: Landsat-8 image synthesis on the blending of Sentinel-1 and MODIS data
Landsat optical sensor is crucial for long-term observations of the Earth's surface with a 30-
m spatial resolution. However, the 16-day revisit cycle and severe atmospheric interference …
m spatial resolution. However, the 16-day revisit cycle and severe atmospheric interference …
Remote Sensing Image Dehazing through an Unsupervised Generative Adversarial Network
L Zhao, Y Yin, T Zhong, Y Jia - Sensors, 2023 - mdpi.com
The degradation of visual quality in remote sensing images caused by haze presents
significant challenges in interpreting and extracting essential information. To effectively …
significant challenges in interpreting and extracting essential information. To effectively …
Cloud-egan: Rethinking cyclegan from a feature enhancement perspective for cloud removal by combining cnn and transformer
Cloud cover presents a major challenge for geoscience research of remote sensing images
with thick clouds causing complete obstruction with information loss while thin clouds …
with thick clouds causing complete obstruction with information loss while thin clouds …
[HTML][HTML] CRformer: Multi-modal data fusion to reconstruct cloud-free optical imagery
Cloud contamination is a common problem in Earth observation that hinders various remote
sensing applications. To address this problem, recent studies have employed deep neural …
sensing applications. To address this problem, recent studies have employed deep neural …
Assessing the Potential of Multi-Temporal Conditional Generative Adversarial Networks in SAR-to-Optical Image Translation for Early-Stage Crop Monitoring
The incomplete construction of optical image time series caused by cloud contamination is
one of the major limitations facing the application of optical satellite images in crop …
one of the major limitations facing the application of optical satellite images in crop …