A partially unsupervised cascade classifier for the analysis of multitemporal remote-sensing images [PDF]
, 2002 A partially unsupervised approach to the classification of multitemporal remote-sensing images is presented. Such an approach allows the automatic classification of a remote-sensing image for which training data are not available, drawing on the ...
Bruzzone, Lorenzo +1 more
core +1 more source
Remote Sensing Upside Down: Exploring the Potential of Ground-Based Multispectral Cameras for Tree Crown Monitoring [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information SciencesRecent advancements in remote sensing have enabled increasingly detailed analysis of forest canopies using a range of platforms, from satellites to ground-based systems.
M. Goebel +3 more
doaj +1 more source
Aggregated Deep Local Features for Remote Sensing Image Retrieval [PDF]
, 2019 Remote Sensing Image Retrieval remains a challenging topic due to the special nature of Remote Sensing Imagery. Such images contain various different semantic objects, which clearly complicates the retrieval task.
Bondarev, Egor +3 more
core +3 more sources
Integrating Crowd-sourced Annotations of Tree Crowns using Markov Random Field and Multispectral Information [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information SciencesBenefiting from advancements in algorithms and computing capabilities, supervised deep learning models offer significant advantages in accurately mapping individual tree canopy cover, which is a fundamental component of forestry management.
Q. Mei, J. Steier, D. Iwaszczuk
doaj +1 more source
International Journal of Applied Earth Observations and Geoinformation, 2023 Extracting difference features is a key technique for polarimetric synthetic aperture radar (PolSAR) image change detection. Although the current PolSAR change detection algorithms based on convolutional neural networks (CNNs) can capture the local ...
Zhifei Yang +4 more
doaj +1 more source
GROUND FILTERING OF CO-REGISTERED MOBILE AND STATIONARY LASER SCANS BY USING SUPERPOINTS IN RANSAC PLANES [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023 Ground filtering is an important tool for many applications. The high variability of landscapes makes it necessary to perform its computation with 3D points as the only input, that is, with as few as possible algorithm parameters and without any training
D. Stütz +4 more
doaj +1 more source
Image fusion techniqes for remote sensing applications [PDF]
, 2002 Image fusion refers to the acquisition, processing and synergistic combination of information provided by various sensors or by the same sensor in many measuring contexts.
Bruzzone, Lorenzo +4 more
core +1 more source
IDENTIFICATION OF MISCLASSIFIED PIXELS IN SEMANTIC SEGMENTATION WITH UNCERTAINTY EVALUATION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2021 Classification, and in particular semantic segmentation, plays a major role in remote sensing. In remote sensing, the classes usually correspond to landcover or landuse types while the data elements are image pixels.
L. E. Budde, D. Bulatov, D. Iwaszczuk
doaj +1 more source
A fast and accurate basis pursuit denoising algorithm with application to super-resolving tomographic SAR [PDF]
, 2018 $L_1$ regularization is used for finding sparse solutions to an underdetermined linear system. As sparse signals are widely expected in remote sensing, this type of regularization scheme and its extensions have been widely employed in many remote sensing
Bamler, Richard +3 more
core +3 more sources
Spatiotemporal Image Fusion in Remote Sensing [PDF]
Remote Sensing, 2019 In this paper, we discuss spatiotemporal data fusion methods in remote sensing. These methods fuse temporally sparse fine-resolution images with temporally dense coarse-resolution images. This review reveals that existing spatiotemporal data fusion methods are mainly dedicated to blending optical images. There is a limited number of studies focusing on
Mariana Belgiu, Alfred Stein
openaire +2 more sources