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06/16/2023
Squeezing nnU-Nets with Knowledge Distillation for On-Board Cloud Detection
Cloud detection is a pivotal satellite image pre-processing step that ca...
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01/26/2023
Multitemporal and multispectral data fusion for super-resolution of Sentinel-2 images
Multispectral Sentinel-2 images are a valuable source of Earth observati...
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10/24/2022
Self-Configuring nnU-Nets Detect Clouds in Satellite Images
Cloud detection is a pivotal satellite image pre-processing step that ca...
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10/06/2022
MuS2: A Benchmark for Sentinel-2 Multi-Image Super-Resolution
Insufficient spatial resolution of satellite imagery, including Sentinel...
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08/03/2022
A Multibranch Convolutional Neural Network for Hyperspectral Unmixing
Hyperspectral unmixing remains one of the most challenging tasks in the ...
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08/03/2022
Graph Neural Networks Extract High-Resolution Cultivated Land Maps from Sentinel-2 Image Series
Maintaining farm sustainability through optimizing the agricultural mana...
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07/27/2019
Segmenting Hyperspectral Images Using Spectral-Spatial Convolutional Neural Networks With Training-Time Data Augmentation
Hyperspectral imaging provides detailed information about the scanned ob...
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07/18/2019
Fully-automated deep learning-powered system for DCE-MRI analysis of brain tumors
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) plays an ...
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06/23/2019
Transfer Learning for Segmenting Dimensionally-Reduced Hyperspectral Images
Deep learning has established the state of the art in multiple fields, i...
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06/16/2019
On training deep networks for satellite image super-resolution
The capabilities of super-resolution reconstruction (SRR)---techniques f...
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03/13/2019
Hyperspectral Data Augmentation
Data augmentation is a popular technique which helps improve generalizat...
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03/01/2019
Deep Learning for Multiple-Image Super-Resolution
Super-resolution reconstruction (SRR) is a process aimed at enhancing sp...
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11/08/2018
