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REMOTE SENSING IMAGE CLASSIFICATION WITH THE SEN12MS DATASET [PDF]

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2021
Abstract. Image classification is one of the main drivers of the rapid developments in deep learning with convolutional neural networks for computer vision. So is the analogous task of scene classification in remote sensing. However, in contrast to the computer vision community that has long been using well-established, large-scale standard datasets to
M. Schmitt, M. Schmitt, Y.-L. Wu
openaire   +4 more sources

Integrating Advanced AI techniques to assist Urban Digital Twins Generation [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Digital twins play a crucial role in autonomous driving applications and transportation system simulations. The need for large scale and dynamic information has increased interest in generating urban digital twins from remote sensing data.
J. Tian, M. Weishaupt, V. Gstaiger, G. Mutreja, C. Amrullah, C. Henry, T. Krauß, P. d'Angelo, S. K. Jangir, S. Auer, F. Kurz, K. Bittner   +11 more
doaj   +1 more source

SyntCities: A Large Synthetic Remote Sensing Dataset for Disparity Estimation

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Studies in the last years have proved the outstanding performance of deep learning for computer vision tasks in the remote sensing field, such as disparity estimation.
Mario Fuentes Reyes, Pablo D'Angelo, Friedrich Fraundorfer   +2 more
doaj   +1 more source

Counting Dense Objects in Remote Sensing Images [PDF]

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020
Estimating accurate number of interested objects from a given image is a challenging yet important task. Significant efforts have been made to address this problem and achieve great progress, yet counting number of ground objects from remote sensing images is barely studied. In this paper, we are interested in counting dense objects from remote sensing
Guangshuai Gao, Qingjie Liu 0001, Yunhong Wang 0001   +2 more
openaire   +3 more sources

PACO: Python-Based Atmospheric Correction

Sensors, 2020
The atmospheric correction of satellite images based on radiative transfer calculations is a prerequisite for many remote sensing applications. The software package ATCOR, developed at the German Aerospace Center (DLR), is a versatile atmospheric ...
Raquel de los Reyes, Maximilian Langheinrich, Peter Schwind, Rudolf Richter, Bringfried Pflug, Martin Bachmann, Rupert Müller, Emiliano Carmona, Viktoria Zekoll, Peter Reinartz   +9 more
doaj   +1 more source

Influence of the Solar Spectra Models on PACO Atmospheric Correction

Remote Sensing, 2022
The solar irradiance is the source of energy used by passive optical remote sensing to measure the ground reflectance and, from there, derive the ground properties.
Raquel De Los Reyes, Rudolf Richter, Martin Bachmann, Kevin Alonso, Bringfried Pflug, Bruno Lafrance, Peter Reinartz   +6 more
doaj   +1 more source

Generating Natural Adversarial Remote Sensing Images [PDF]

IEEE Transactions on Geoscience and Remote Sensing, 2022
Over the last years, Remote Sensing Images (RSI) analysis have started resorting to using deep neural networks to solve most of the commonly faced problems, such as detection, land cover classification or segmentation. As far as critical decision making can be based upon the results of RSI analysis, it is important to clearly identify and understand ...
Jean-Christophe Burnel, Kilian Fatras, Rémi Flamary, Nicolas Courty   +3 more
openaire   +4 more sources

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

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

Remote Sensing Image Haze Removal Based on Superpixel

, 2023
The presence of haze significantly degrades the quality of remote sensing images, resulting in issues such as color distortion, reduced contrast, loss of texture, and blurred image edges, which can ultimately lead to the failure of remote sensing ...
Tiecheng Bai, Yufeng He, Cuili Li
core   +1 more source