Search Results

Automated detection of rock glaciers using deep learning and object-based image analysis

by Robson, Benjamin Aubrey, Bolch, Tobias, MacDonell, Shelley, Hölbling, Daniel, Rastner, Philipp, Schaffer, Nicole
Published in Remote Sensing of Environment (2020)

Automated detection of rock glaciers using deep learning and object-based image analysis

by Robson, Benjamin Aubrey, Bolch, Tobias, MacDonell, Shelley, Hölbling, Daniel, Rastner, Philipp, Schaffer, Nicole
Published 2020

Image classification of marine-terminating outlet glaciers in Greenland using deep learning methods

by Marochov, Melanie, Stokes, Chris R., Carbonneau, Patrice E.
Published in The Cryosphere (2021)

On the detection and segmentation of metocean features on SAR images using Deep Learning: perspectives for SWOT

by Longépé, Nicolas, Husson, Romain, Wang, Chen, Mouche, Alexis, Tandeo, Pierre
Published 2019

On the detection and segmentation of metocean features on SAR images using Deep Learning: perspectives for SWOT

by Longépé, Nicolas, Husson, Romain, Wang, Chen, Mouche, Alexis, Tandeo, Pierre
Published 2019

APPLICATION OF DEEP LEARNING TECHNOLOGIES FOR STUDYING THIN SECTIONS ON THE EXAMPLE OF USINSK OIL FIELD

by Nikita A. Popov, Ivan S. Putilov, Anastasiya A. Gulyaeva, Ekaterina V. Vinokurova
Published in Izvestiya Tomskogo Politekhnicheskogo Universiteta Inziniring Georesursov (2020)

Image classification of marine-terminating outlet glaciers in Greenland using deep learning methods

by Marochov, Melanie, Stokes, Chris R., Carbonneau, Patrice E.
Published in The Cryosphere (2021)

Evaluating a deep learning approach for mapping retrogressive thaw slumps across the Arctic

by Nitze, Ingmar, Heidler, Konrad, Barth, Sophia, Targowicka, Alexandra, Guido, Grosse
Published 2021

Large-Scale Detection and Categorization of Oil Spills from SAR Images with Deep Learning

by Bianchi, Filippo Maria, Espeseth, Martine, Borch, Njål Trygve
Published in Remote Sensing (2020)

Deep learning for mapping retrogressive thaw slumps and landslides across the Arctic permafrost domain

by Nitze, Ingmar, Heidler, Konrad, Barth, Sophia, Grosse, Guido
Published 2022

Evaluating a deep-learning approach for mapping retrogressive thaw slumps across the Arctic

by Nitze, Ingmar, Heidler, Konrad, Barth, Sophia, Guido, Grosse, Targowicka, Alexandra
Published 2021

Newly reconstructed Arctic surface air temperatures for 1979–2021 with deep learning method

by Ziqi Ma, Jianbin Huang, Xiangdong Zhang, Yong Luo, Minghu Ding, Jun Wen, Weixin Jin, Chen Qiao, Yifu Yin
Published in Scientific Data (2023)

Newly reconstructed Arctic surface air temperatures for 1979–2021 with deep learning method

by Ma, Ziqi, Huang, Jianbin, Zhang, Xiangdong, Luo, Yong, Ding, Minghu, Wen, Jun, Jin, Weixin, Qiao, Chen, Yin, Yifu
Published in Scientific Data (2023)

Code associated with the paper: 'Seasonal Arctic sea ice forecasting with probabilistic deep learning'

by Tom R. Andersson
Published 2021

Code associated with the paper: 'Seasonal Arctic sea ice forecasting with probabilistic deep learning'

by Andersson, Tom R.
Published 2021

Code associated with the paper: 'Seasonal Arctic sea ice forecasting with probabilistic deep learning'

by Andersson, Tom R.
Published 2021

Automatic flower detection and phenology monitoring using time‐lapse cameras and deep learning

by Hjalte M. R. Mann, Alexandros Iosifidis, Jane U. Jepsen, Jeffrey M. Welker, Maarten J. J. E. Loonen, Toke T. Høye
Published in Remote Sensing in Ecology and Conservation (2022)

Automatic flower detection and phenology monitoring using time-lapse cameras and deep learning

by Mann, Hjalte M.R., Iosifidis, Alexandros, Jepsen, Jane U., Welker, Jeffrey M., Loonen, Maarten J.J.E., Høye, Toke T.
Published in Remote Sensing in Ecology and Conservation (2022)

Automatic flower detection and phenology monitoring using time-lapse cameras and deep learning

by Mann, Hjalte M. R., Iosifidis, Alexandros, Jepsen, Jane U., Welker, Jeffrey M., Loonen, Maarten J. J., Høye, Toke T.
Published 2022

Exploiting more robust and efficacious deep learning techniques for modeling wind power with speed

by Hao Chen, Reidar Staupe-Delgado
Published in Energy Reports (2022)