Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Helber, Patrick"'
Autor:
Mena, Francisco, Pathak, Deepak, Najjar, Hiba, Sanchez, Cristhian, Helber, Patrick, Bischke, Benjamin, Habelitz, Peter, Miranda, Miro, Siddamsetty, Jayanth, Nuske, Marlon, Charfuelan, Marcela, Arenas, Diego, Vollmer, Michaela, Dengel, Andreas
Accurate crop yield prediction is of utmost importance for informed decision-making in agriculture, aiding farmers, and industry stakeholders. However, this task is complex and depends on multiple factors, such as environmental conditions, soil prope
Externí odkaz:
http://arxiv.org/abs/2401.11844
Autor:
Pathak, Deepak, Miranda, Miro, Mena, Francisco, Sanchez, Cristhian, Helber, Patrick, Bischke, Benjamin, Habelitz, Peter, Najjar, Hiba, Siddamsetty, Jayanth, Arenas, Diego, Vollmer, Michaela, Charfuelan, Marcela, Nuske, Marlon, Dengel, Andreas
We introduce a simple yet effective early fusion method for crop yield prediction that handles multiple input modalities with different temporal and spatial resolutions. We use high-resolution crop yield maps as ground truth data to train crop and ma
Externí odkaz:
http://arxiv.org/abs/2308.08948
RapidAI4EO: Mono- and Multi-temporal Deep Learning models for Updating the CORINE Land Cover Product
Autor:
Bhugra, Priyash, Bischke, Benjamin, Werner, Christoph, Syrnicki, Robert, Packbier, Carolin, Helber, Patrick, Senaras, Caglar, Rana, Akhil Singh, Davis, Tim, De Keersmaecker, Wanda, Zanaga, Daniele, Wania, Annett, Van De Kerchove, Ruben, Marchisio, Giovanni
In the remote sensing community, Land Use Land Cover (LULC) classification with satellite imagery is a main focus of current research activities. Accurate and appropriate LULC classification, however, continues to be a challenging task. In this paper
Externí odkaz:
http://arxiv.org/abs/2210.14624
Autor:
Marchisio, Giovanni, Helber, Patrick, Bischke, Benjamin, Davis, Timothy, Senaras, Caglar, Zanaga, Daniele, Van De Kerchove, Ruben, Wania, Annett
Under the sponsorship of the European Union Horizon 2020 program, RapidAI4EO will establish the foundations for the next generation of Copernicus Land Monitoring Service (CLMS) products. The project aims to provide intensified monitoring of Land Use
Externí odkaz:
http://arxiv.org/abs/2110.01919
Autor:
Gram-Hansen, Bradley, Helber, Patrick, Varatharajan, Indhu, Azam, Faiza, Coca-Castro, Alejandro, Kopackova, Veronika, Bilinski, Piotr
Publikováno v:
AAAI/ACM Conference on AI, Ethics, and Society (AIES 2019)
Informal settlements are home to the most socially and economically vulnerable people on the planet. In order to deliver effective economic and social aid, non-government organizations (NGOs), such as the United Nations Children's Fund (UNICEF), requ
Externí odkaz:
http://arxiv.org/abs/1901.00861
Autor:
Helber, Patrick, Gram-Hansen, Bradley, Varatharajan, Indhu, Azam, Faiza, Coca-Castro, Alejandro, Kopackova, Veronika, Bilinski, Piotr
Detecting and mapping informal settlements encompasses several of the United Nations sustainable development goals. This is because informal settlements are home to the most socially and economically vulnerable people on the planet. Thus, understandi
Externí odkaz:
http://arxiv.org/abs/1812.00812
Autor:
Helber, Patrick, Gram-Hansen, Bradley, Varatharajan, Indhu, Azam, Faiza, Coca-Castro, Alejandro, Kopackova, Veronika, Bilinski, Piotr
Publikováno v:
NeurlPS workshop on Machine Learning for the Developing World (ML4DW), 2018
Detecting and mapping informal settlements encompasses several of the United Nations sustainable development goals. This is because informal settlements are home to the most socially and economically vulnerable people on the planet. Thus, understandi
Externí odkaz:
http://arxiv.org/abs/1812.00786
The integration of information acquired with different modalities, spatial resolution and spectral bands has shown to improve predictive accuracies. Data fusion is therefore one of the key challenges in remote sensing. Most prior work focusing on mul
Externí odkaz:
http://arxiv.org/abs/1808.03195
The increased availability of high resolution satellite imagery allows to sense very detailed structures on the surface of our planet. Access to such information opens up new directions in the analysis of remote sensing imagery. However, at the same
Externí odkaz:
http://arxiv.org/abs/1709.05932