Hierarchical Segmentation of Multiresolution Remote Sensing Images [PDF]
The extraction of urban patterns from very high spatial resolution optical images presents challenges related to the size, the accuracy and the complexity of the data. In order to efficiently carry out this task, a multiresolution hierarchical approach is proposed. It enables to progressively segment several images (of increasing resolutions) of a same
Kurtz, Camille +3 more
openaire +3 more sources
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos +2 more
wiley +1 more source
Deep Residual Squeeze and Excitation Network for Remote Sensing Image Super-Resolution
Recently, deep convolutional neural networks (DCNN) have obtained promising results in single image super-resolution (SISR) of remote sensing images. Due to the high complexity of remote sensing image distribution, most of the existing methods are not ...
Jun Gu +4 more
core +1 more source
Unsupervised Remote Sensing Image Super-Resolution Guided by Visible Images
Remote sensing images are widely used in many applications. However, due to being limited by the sensors, it is difficult to obtain high-resolution (HR) images from remote sensing images.
Jianxiang Li +3 more
core +1 more source
A Lightweight Procedural Layer for Hybrid Experimental–Computational Workflows in Materials Science
We unveil a prototype hybrid‐workflow framework that fuses automatedcomputation with hands‐on experiments. Built atop pyiron, a lightweight, parameterized layer translates procedure descriptions into executable manual steps, syncing instrument settings, human interventions, and data capture in real‐time today.
Steffen Brinckmann +8 more
wiley +1 more source
Iterative Random Training Sampling Spectral Spatial Classification for Hyperspectral Images
Hyperspectral image classification (HSIC) has generated considerable interests over the past years. However, one of challenging issues arising in HSIC is inconsistent classification, which is mainly caused by random training sampling (RTS) of selecting ...
Chein-I Chang +5 more
doaj +1 more source
PASTA‐ELN: Simplifying Research Data Management for Experimental Materials Science
Research data management faces ongoing hurdles as many ELNs remain complex and restrictive. PASTA‐ELN offers an open‐source, cross‐platform solution that prioritizes simplicity, offline access, and user control. Its in tuitive folder structure, modular Python add‐ons, and open formats enable seamless documentation, FAIR data practices, and easy ...
S. Brinckmann, G. Winkens, R. Schwaiger
wiley +1 more source
An urban classification approach based on an object-oriented analysis of high resolution satellite imagery for a spatial structuring within urban areas [PDF]
Classifying the complex structures of urban morphology from high resolution remote sensing imagery comprises difficulties due to their spectral and spatial heterogeneity.
Taubenböck, Hannes +2 more
core
Blind Remote Sensing Image Deblurring Using Local Binary Pattern Prior
In this paper, an algorithm based on local binary pattern (LBP) is proposed to obtain clear remote sensing images under the premise of unknown causes of blurring.
Yongjie Piao +6 more
core +1 more source
Operational Deformation Monitoring of the Hong Kong–Zhuhai–Macao Bridge with Multi-Orbit LuTan-1 SAR Satellites [PDF]
This study evaluates the operational capability of the Chinese LuTan-1 (LT-1) L-band SAR constellation for monitoring the Hong Kong–Zhuhai–Macao Bridge (HZMB), a representative sea-crossing bridge under a complex subtropical marine climate ...
J. Lu +7 more
doaj +1 more source

