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pro vyhledávání: '"Karatsiolis, Savvas"'
The widespread use of black-box AI models has raised the need for algorithms and methods that explain the decisions made by these models. In recent years, the AI research community is increasingly interested in models' explainability since black-box
Externí odkaz:
http://arxiv.org/abs/2209.08906
Despite the plethora of successful Super-Resolution Reconstruction (SRR) models applied to natural images, their application to remote sensing imagery tends to produce poor results. Remote sensing imagery is often more complicated than natural images
Externí odkaz:
http://arxiv.org/abs/2205.04056
Estimating the heightmaps of buildings and vegetation in single remotely sensed images is a challenging problem. Effective solutions to this problem can comprise the stepping stone for solving complex and demanding problems that require 3D informatio
Externí odkaz:
http://arxiv.org/abs/2104.10874
Autor:
Kamilaris, Andreas, Filippi, Jean-Baptiste, Padubidri, Chirag, Provoost, Jesper, Karatsiolis, Savvas, Cole, Ian, Couwenbergh, Wouter, Demetriou, Evi
Over the past couple of decades, the number of wildfires and area of land burned around the world has been steadily increasing, partly due to climatic changes and global warming. Therefore, there is a high probability that more people will be exposed
Externí odkaz:
http://arxiv.org/abs/2102.11558
A challenge of the computer vision community is to understand the semantics of an image, in order to allow image reconstruction based on existing high-level features or to better analyze (semi-)labelled datasets. Towards addressing this challenge, th
Externí odkaz:
http://arxiv.org/abs/2008.00665
Autor:
Kentsch, Sarah, Karatsiolis, Savvas, Kamilaris, Andreas, Tomhave, Luca, Caceres, Maximo Larry Lopez
Natural forests are complex ecosystems whose tree species distribution and their ecosystem functions are still not well understood. Sustainable management of these forests is of high importance because of their significant role in climate regulation,
Externí odkaz:
http://arxiv.org/abs/2007.08907
This paper describes preliminary work in the recent promising approach of generating synthetic training data for facilitating the learning procedure of deep learning (DL) models, with a focus on aerial photos produced by unmanned aerial vehicles (UAV
Externí odkaz:
http://arxiv.org/abs/1908.06472
Autor:
Karatsiolis, Savvas1 (AUTHOR) c.padubidri@cyens.org.cy, Padubidri, Chirag1 (AUTHOR) a.kamilaris@cyens.org.cy, Kamilaris, Andreas1,2 (AUTHOR)
Publikováno v:
Remote Sensing. Jan2024, Vol. 16 Issue 1, p142. 21p.
Autor:
Karatsiolis, Savvas1 (AUTHOR) skarat01@cs.ucy.ac.cy, Schizas, Christos N.1 (AUTHOR), Petkov, Nicolai2 (AUTHOR)
Publikováno v:
Neural Computing & Applications. Jun2020, Vol. 32 Issue 11, p6779-6791. 13p.
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