Zobrazeno 1 - 10
of 51
pro vyhledávání: '"Mullissa, Adugna"'
Autor:
Mullissa, Adugna, Saatchi, Sassan
Tropical forests play an important role in regulating the global carbon cycle and are crucial for maintaining the tropical forest biodiversity. Therefore, there is an urgent need to map the extent of tropical forest ecosystems. Recently, deep learnin
Externí odkaz:
http://arxiv.org/abs/2408.00107
Autor:
Wagner, Fabien H, Favrichon, Samuel, Dalagnol, Ricardo, Hirye, Mayumi CM, Mullissa, Adugna, Saatchi, Sassan
The Amazon, the world's largest rainforest, faces a severe historic drought. The Rio Negro River, one of the major Amazon River tributaries, reaches its lowest level in a century in October 2023. Here, we used a U-net deep learning model to map water
Externí odkaz:
http://arxiv.org/abs/2401.16393
Autor:
Mullissa, Adugna1,2 (AUTHOR) amullissa@ctrees.org, Saatchi, Sassan1,2,3 (AUTHOR), Dalagnol, Ricardo1,2,3 (AUTHOR), Erickson, Tyler4 (AUTHOR) tyler@vorgeo.com, Provost, Naomi1 (AUTHOR), Osborn, Fiona1 (AUTHOR), Ashary, Aleena1 (AUTHOR), Moon, Violet1 (AUTHOR), Melling, Daniel1 (AUTHOR)
Publikováno v:
Remote Sensing. Jun2024, Vol. 16 Issue 12, p2151. 16p.
Autor:
Gaso, Deborah V., Paudel, Dilli, de Wit, Allard, Puntel, Laila A., Mullissa, Adugna, Kooistra, Lammert
Publikováno v:
In Agricultural and Forest Meteorology 15 May 2024 351
A Polarimetric Synthetic Aperture Radar (PolSAR) sensor is able to collect images in different polarization states, making it a rich source of information for target characterization. PolSAR images are inherently affected by speckle. Therefore, befor
Externí odkaz:
http://arxiv.org/abs/2103.07394
Deep learning (DL) has proven to be a suitable approach for despeckling synthetic aperture radar (SAR) images. So far, most DL models are trained to reduce speckle that follows a particular distribution, either using simulated noise or a specific set
Externí odkaz:
http://arxiv.org/abs/2012.03066
Publikováno v:
In Remote Sensing of Environment 1 December 2023 298
Autor:
Moraiti, Nikoletta1 (AUTHOR) amullissa@ucla.edu, Mullissa, Adugna1,2,3 (AUTHOR) johannes.reiche@wur.nl, Rahn, Eric4 (AUTHOR) e.rahn@cgiar.org, Sassen, Marieke5 (AUTHOR) marieke.sassen@wur.nl, Reiche, Johannes1 (AUTHOR)
Publikováno v:
Remote Sensing. Feb2024, Vol. 16 Issue 3, p598. 32p.
Autor:
Slagter, Bart, Reiche, Johannes, Marcos, Diego, Mullissa, Adugna, Lossou, Etse, Peña-Claros, Marielos, Herold, Martin
Publikováno v:
In Remote Sensing of Environment 1 September 2023 295
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