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2061by Sergey Korolev, Aleksei Sorokin, Igor Urmanov, Aleksandr Kamaev, Olga Girina“... of images with documented eruptions allow us to use modern deep learning technologies for whole frame...”
Published in Remote Sensing (2021)
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2062“... with multiple deep learning models to prove the effectiveness of such predictability evaluation method...”
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2063“... resources further. In this paper, we propose a new specific deep-learning method called high-resolution...”
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2064“..., it is difficult for many deep learning-based segmentation algorithms to achieve accurate ice–water segmentation...”
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2065“... of the machine learning methods. Future studies should use deep learning methods to take full advantage...”
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2066by Ziyue Dai, Huimin Li, Chen Wang, Yijun He“.... The global percentage map of directly identified rain cells is consistent with the deep-learning results...”
Published in Journal of Marine Science and Engineering (2022)
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2067by Xiaolun Chen, Xiaowen Luo, Ziyin Wu, Xiaoming Qin, Jihong Shang, Bin Li, Mingwei Wang, Hongyang Wan“... the advantages of satellite altimetry-derived and multibeam sonar-derived bathymetry, we apply deep learning...”
Published in Remote Sensing (2022)
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2068“... in the region poleward from 85°S have been mapped in Lunar Reconnaissance Orbiter's NAC imagery using a deep...”
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2069Robust Autonomous Vehicle Computer-Vision-Based Localization in Challenging Environmental Conditionsby Sergei Chuprov, Pavel Belyaev, Ruslan Gataullin, Leon Reznik, Evgenii Neverov, Ilia Viksnin“... in robotic and AV computer vision, as well as deep learning applications. Our empirical study showed...”
Published in Applied Sciences (2023)
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2070“... and an unsupervised trained high-resource deep learning approach, respectively. In both architectures state-based...”
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2071by Zachary L. Langford, Jitendra Kumar, Forrest M. Hoffman, Amy L. Breen, Colleen M. Iversen“... darkness, and poor availability of high-resolution imagery. A multi-sensor remote sensing-based deep...”
Published in Remote Sensing (2019)
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2072by Buus-Hinkler, Jørgen, Wulf, Tore, Stokholm, Andreas Rønne, Korosov, Anton, Saldo, Roberto, Pedersen, Leif Toudal, Arthurs, David, Solberg, Rune, Longépé, Nicolas, Brandt Kreiner, Matilde“... by the European Space Agency (ESA) ɸ-lab. The purpose of the competition is to develop deep learning models...”
Published 2023
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2073by Buus-Hinkler, Jørgen, Wulf, Tore, Stokholm, Andreas Rønne, Korosov, Anton, Saldo, Roberto, Pedersen, Leif Toudal, Arthurs, David, Solberg, Rune, Longépé, Nicolas, Brandt Kreiner, Matilde“... by the European Space Agency (ESA) ɸ-lab. The purpose of the competition is to develop deep learning models...”
Published 2023
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2074by Buus-Hinkler, Jørgen, Wulf, Tore, Stokholm, Andreas Rønne, Korosov, Anton, Saldo, Roberto, Pedersen, Leif Toudal, Arthurs, David, Solberg, Rune, Longépé, Nicolas, Brandt Kreiner, Matilde“... by the European Space Agency (ESA) ɸ-lab. The purpose of the competition is to develop deep learning models...”
Published 2023
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2075by Buus-Hinkler, Jørgen, Wulf, Tore, Stokholm, Andreas Rønne, Korosov, Anton, Saldo, Roberto, Pedersen, Leif Toudal, Arthurs, David, Solberg, Rune, Longépé, Nicolas, Brandt Kreiner, Matilde“... by the European Space Agency (ESA) ɸ-lab. The purpose of the competition is to develop deep learning models...”
Published 2023
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2076by Dumitru, Corneliu Octavian, Schwarz, Gottfried, Dax, Gabriel, Vlad, Andrei, Ao, Dongyang, Datcu, Mihai“... combine current machine learning algorithms with new approaches, we can see how current deep learning...”
Published 2020
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2077by Beise, J, Glaser, C, Anker, A, Baldi, P, Barwick, SW, Bernhoff, H, Besson, DZ, Bingefors, N, Cataldo, M, Chen, P, Fernández, DG, Gaswint, G, Hallgren, A, Hallmann, S, Hanson, JC, Klein, SR, Kleinfelder, SA, Lahmann, R, Liu, J, Magnuson, M, McAleer, S, Meyers, Z, Nam, J, Nelles, A, Novikov, A, Paul, MP, Persichilli, C, Plaisier, I, Pyras, L, Rice-Smith, R, Tatar, J, Wang, SH, Welling, C, Zhao, L“... (including deep learning). This constitutes an in-situ test of the neutrino vertex distance reconstruction...”
Published 2022
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2078“... understanding of ice–ocean interactions and also necessitates the automation of terminus delineation. While deep...”
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2079by Zhong, Ming, Torterotot, Maelle, Branch, Trevor A., Stafford, Kathleen M., Royer, Jean-yves, Dodhia, Rahul, Lavista Ferres, Juan“... the underwater hydrophones in the Indian Ocean to build a deep learning model to detect, classify, and count...”
Published in The Journal of the Acoustical Society of America (2021)
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2080by Ren, Yibin, Li, Xiaofeng, Yang, Xiaofeng, Xu, Huan“...This study develops a deep learning (DL) model to classify the sea ice and open water from...”
Published in IEEE Geoscience and Remote Sensing Letters (2022)
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