Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Teodora Selea"'
Autor:
Teodora Selea
Publikováno v:
Remote Sensing, Vol 15, Iss 12, p 2980 (2023)
With the increasing volume of collected Earth observation (EO) data, artificial intelligence (AI) methods have become state-of-the-art in processing and analyzing them. However, there is still a lack of high-quality, large-scale EO datasets for train
Externí odkaz:
https://doaj.org/article/26952d32de224b5186bf76b42f2d084f
Deep Learning is an extremely important research topic in Earth Observation. Current use-cases range from semantic image segmentation, object detection to more common problems found in computer vision such as object identification. Earth Observation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::91447bda7a5a6cdbc0fed4df342dba9a
https://doi.org/10.20944/preprints202211.0226.v1
https://doi.org/10.20944/preprints202211.0226.v1
Autor:
Marius-Florin Pslaru, Teodora Selea
Publikováno v:
SYNASC
The large amount of collected data in the field of Earth Observation has created the need for automatization in processing and extraction information from it. Thus, deep learning (DL) techniques have gained popularity among the remote sensing communi
Publikováno v:
ICCP
In this article we present a Proof-Of-Concept distributed system designed for supporting a Regional Earth Observation Platform, particularly the use-cases from the ESA Pathfinder EO4SEE Project. The described system is designed adhering to the ESA Th
Autor:
Oana Brandibur, Eva Kaslik, Daniela Zaharie, Madalina Erascu, Marc Frincu, Anca Vulpe, Teodora Selea
Publikováno v:
AIP Conference Proceedings.
Publikováno v:
Heterogeneity, High Performance Computing, Self-Organization and the Cloud ISBN: 9783319760377
In the context of creating a self-organising and self-managing cloud infrastructure we propose a set of extensions to the existing Service Description Languages (SDLs) and Application Blueprints in order to establish a common ground for the various C
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c56b54b8a1feaba4cb0661287881e56f
https://doi.org/10.1007/978-3-319-76038-4_4
https://doi.org/10.1007/978-3-319-76038-4_4
Publikováno v:
Modeling and Simulation in HPC and Cloud Systems
Studies in Big Data ISBN: 9783319737669
Studies in Big Data
Studies in Big Data-Modeling and Simulation in HPC and Cloud Systems
Studies in Big Data ISBN: 9783319737669
Studies in Big Data
Studies in Big Data-Modeling and Simulation in HPC and Cloud Systems
Evaluating the performance of distributed applications can be performed by in situ deployment on real-life platforms. However, this technique requires effort in terms of time allocated to configure both application and platform, execution time of tes
Autor:
Marian Neagul, Teodora Selea
Publikováno v:
SYNASC
In this paper we aim to investigate different deep learning techniques for automatic extraction of valuable information from large sized satellite image data. We focus on the problem of semantic segmentation which attaches a class label to each pixel
Publikováno v:
Proceedings of the 1st International Workshop on Next generation of Cloud Architectures-CloudNG:17
Proceedings of the 1st International Workshop on Next generation of Cloud Architectures
CloudNG@EuroSys
Proceedings of the 1st International Workshop on Next generation of Cloud Architectures
CloudNG@EuroSys
Deploying applications which require computational power or data intensive capabilities into a cloud environment might became overwhelming, due to the diversity of cloud services and resources. CloudLightning allows users to design their application
Publikováno v:
CCGrid
2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid)
2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid)
The envisioned intercloud bridging numerous cloud providers offering clients the ability to run their applications on specific configurations unavailable to single clouds poses challenges with respect to selecting the appropriate resources for deploy