Results 31 to 40 of about 353,115 (201)

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, Fernandez Prieto, Diego   +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 Sciences
Recent 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, L. Wolf, F. Packwitz, D. Iwaszczuk   +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, de With, Peter H. N., Imbriaco, Raffaele, Sebastian, Clint   +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 Sciences
Benefiting 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

Unsupervised change detection in PolSAR images using siamese encoder–decoder framework based on graph-context attention network

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, Yan Wu, Ming Li, Xin Hu, Zhikang Li   +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, J. Li, J. Li, J. Huai, D. Bulatov   +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, Farina, Alfonso, Morabito, Francesco, Serpico, Sebastiano Bruno, Simone, Giovanni   +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

AN EVALUATION OF STEREO AND MULTIVIEW ALGORITHMS FOR 3D RECONSTRUCTION WITH SYNTHETIC DATA [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023
The reconstruction of 3D scenes from images has usually been addressed with two different strategies, namely stereo and multiview. The former requires rectified images and generates a disparity map, while the latter relies on the camera parameters and ...
M. Fuentes Reyes, P. d’Angelo, F. Fraundorfer, F. Fraundorfer   +3 more
doaj   +1 more source

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