Search Results for author:
Found 6 papers, 6 papers with code
Change Detection in VHR Imagery With Severe Co-Registration Errors Using Deep Learning: A Comparative Study
Based on that, the goal of this study is to evaluate the performance of five state-of-the-art DL CD methods, two unsupervised and three supervised, on VHR images with severe co-registration errors.
Change Detection
Change detection for remote sensing images
+1
Pansharpening PRISMA Data for Marine Plastic Litter Detection Using Plastic Indexes
The required pre-processing steps have been defined and 13 pansharpening methods have been applied and evaluated for their ability to spectrally discriminate plastics from water.
Hyperspectral Image Super-Resolution
Image Super-Resolution
+1
Convolutional neural networks for detecting challenging cases in cloud masking using Sentinel-2 imagery
Cloud contamination represents a large obstacle for mapping the earth’s surface using remotely sensed data.
Increasing the Sentinel-2 potential for marine plastic litter monitoring through image fusion techniques
Sentinel-2 (S2) images have been used in several projects to detect large accumulations of marine litter and plastic targets.
Fine-Tuning Self-Organizing Maps for Sentinel-2 Imagery: Separating Clouds from Bright Surfaces
This study evaluated a SOM for cloud masking Sentinel-2 images and proposed a fine-tuning methodology to separate clouds from bright land areas.
Artificial neural networks for cloud masking of Sentinel-2 ocean images with noise and sunglint
It was shown that the ANNs trained on the second dataset perform very favourably, in contrast to the ANNs trained on the first dataset that fails to adequately represent the spectra of the noisy Sentinel-2 images.
