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Artykuły w czasopismach na temat "Heterogeneous oceanic data"
Jourdin, F., O. Francis, P. Vincent i P. Mazzega. "Some results of heterogeneous data inversions for oceanic tides". Journal of Geophysical Research: Solid Earth 96, B12 (10.11.1991): 20267–88. http://dx.doi.org/10.1029/91jb00426.
Pełny tekst źródłaSun, L. Charles. "Data Inter-Operability Driven by Oceanic Data Assimilation Needs". Marine Technology Society Journal 33, nr 3 (1.01.1999): 55–66. http://dx.doi.org/10.4031/mtsj.33.3.7.
Pełny tekst źródłaChen, Shan-Tai, Shung-Lin Dou i Wann-Jin Chen. "A Data Mining Approach to Rainfall Intensity Classification Using TRMM/TMI Data". Journal of Advanced Computational Intelligence and Intelligent Informatics 12, nr 6 (20.11.2008): 516–22. http://dx.doi.org/10.20965/jaciii.2008.p0516.
Pełny tekst źródłaYi, Shuang, i Kosuke Heki. "Heterogeneous oceanic mass distribution in GRACE observations and its leakage effect". Geophysical Journal International 221, nr 1 (10.01.2020): 603–16. http://dx.doi.org/10.1093/gji/ggaa022.
Pełny tekst źródłaSokolov, S. D., G. Ye Bondarenko, A. K. Khudoley, O. L. Morozov, M. V. Luchitskaya, M. I. Tuchkova i P. W. Layer. "Tectonic reconstruction of Uda-Murgal arc and the Late Jurassic and Early Cretaceous convergent margin of Northeast Asia–Northwest Pacific". Stephan Mueller Special Publication Series 4 (17.09.2009): 273–88. http://dx.doi.org/10.5194/smsps-4-273-2009.
Pełny tekst źródłaPiontkovski, S. A., I. A. Minsky i Ya V. Meger. "LONG-TERM VARIABILITY OF OCEANIC ZOOPLANKTON BIOMASS". Водные биоресурсы и среда обитания 6, nr 3 (2023): 52–65. http://dx.doi.org/10.47921/2619-1024_2023_6_3_52.
Pełny tekst źródłaBoev, Blažo, Vladica Cvetković, Dejan Prelević, Kristina Šarić i Ivan Boev. "EAST VARDAR OPHIOLITES REVISITED: A BRIEF SYNTHESIS OF GEOLOGY AND GEOCHEMICAL DATA". Contributions, Section of Natural, Mathematical and Biotechnical Sciences 39, nr 1 (2.07.2018): 51. http://dx.doi.org/10.20903/csnmbs.masa.2018.39.1.119.
Pełny tekst źródłaKotowski, Alissa J., i Whitney M. Behr. "Length scales and types of heterogeneities along the deep subduction interface: Insights from exhumed rocks on Syros Island, Greece". Geosphere 15, nr 4 (24.06.2019): 1038–65. http://dx.doi.org/10.1130/ges02037.1.
Pełny tekst źródłaSrivastava, Rohit, i Ruchita Shah. "Study of Monsoonal Features Using Regional Climate Model over Heterogeneous Monsoon Dominated Region". E3S Web of Conferences 101 (2019): 03004. http://dx.doi.org/10.1051/e3sconf/201910103004.
Pełny tekst źródłaLücke, O. H., i I. G. Arroyo. "Density structure and geometry of the Costa Rican subduction zone from 3-D gravity modeling and local earthquake data". Solid Earth Discussions 7, nr 3 (14.07.2015): 1941–77. http://dx.doi.org/10.5194/sed-7-1941-2015.
Pełny tekst źródłaRozprawy doktorskie na temat "Heterogeneous oceanic data"
Zambra, Matteo. "Méthodes IA multimodales dans des contextes d’observation océanographique et de surveillance maritime multi-capteurs hétérogènes". Electronic Thesis or Diss., Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2024. http://www.theses.fr/2024IMTA0391.
Pełny tekst źródłaThe aim of this thesis is to study the simultaneous use of heterogeneous ocean datasets to improve the performance of predictive models used in scientific and operational fields for the simulation and analysis of the ocean and marine environment. Two distinct case studies were explored in the course of the thesis work. The first study focuses on the local estimation of wind speed at the sea surface from underwater soundscape measurements and atmospheric model products. The second study considers the spatial extension of the problem and the use of observations at different scales and spatial resolutions, from pseudo-observations simulating satellite images to time series measured by in-situ infrastructures. The recurring theme of these investigations is the multi-modality of the data fed into the model. That is, to what extent and how the predictive model can benefit from the use of spatio-temporally heterogeneous information channels. The preferred methodological tool is a simulation system based on variational data assimilation and deep learning concepts
Części książek na temat "Heterogeneous oceanic data"
Sims, K. W. W., H. E. Newsom i E. S. Gladney. "Chemical Fractionation During Formation Of The Earth’s Core And Continental Crust: Clues From As, Sb, W, And Mo". W Origin of the Earth, 291–317. Oxford University PressNew York, NY, 1990. http://dx.doi.org/10.1093/oso/9780195066197.003.0017.
Pełny tekst źródłaAlegret, Laia, Gabriela J. Arreguín-Rodríguez i Ellen Thomas. "Oceanic productivity after the Cretaceous/Paleogene impact: Where do we stand? The view from the deep". W From the Guajira Desert to the Apennines, and from Mediterranean Microplates to the Mexican Killer Asteroid: Honoring the Career of Walter Alvarez. Geological Society of America, 2022. http://dx.doi.org/10.1130/2022.2557(21).
Pełny tekst źródłaVignudelli, Stefano, i Francesco De Biasio. "Coastal Sea Level Trends from a Joint Use of Satellite Radar Altimetry, GPS and Tide Gauges: Case Study of the Northern Adriatic Sea". W Geodetic Sciences - Theory, Applications and Recent Developments. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.98243.
Pełny tekst źródłaCaselli, Graziella, i Sven Drefahl. "Future Mortality in Low Mortality Countries". W World Population & Human Capital in the Twenty-First Century. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198813422.003.0009.
Pełny tekst źródłaStreszczenia konferencji na temat "Heterogeneous oceanic data"
Pinto, Jose, Paulo Sousa Dias, Joao Borges Sousa i Fernando L. Pereira. "Large scale data collection using networks of heterogeneous vehicles and sensors". W OCEANS 2009-EUROPE (OCEANS). IEEE, 2009. http://dx.doi.org/10.1109/oceanse.2009.5278239.
Pełny tekst źródłaVanMiddlesworth, Mark. "A heterogeneous rapid-turnaround visualization package for AUV data". W OCEANS 2011 - SPAIN. IEEE, 2011. http://dx.doi.org/10.1109/oceans-spain.2011.6003655.
Pełny tekst źródłaRong, Tian, ChenXu Wang, QingHua Luo i YingChun Li. "Underwater shipwreck target detection based on audio-visual heterogeneous data". W OCEANS 2023 - Limerick. IEEE, 2023. http://dx.doi.org/10.1109/oceanslimerick52467.2023.10244537.
Pełny tekst źródłaCamossi, Elena, Raffaele Grasso, Gabriele Ferri, Alessandro Faggiani, Kevin LePage i Sandro Carniel. "Maritime Linked Data for Situational Awareness Heterogeneous Sensor Networks". W OCEANS 2021: San Diego – Porto. IEEE, 2021. http://dx.doi.org/10.23919/oceans44145.2021.9705759.
Pełny tekst źródłaFalchetti, Silvia, Alberto Alvarez i Reiner Onken. "A relocatable EnKF ocean data assimilation tool for heterogeneous observational networks". W OCEANS 2015 - Genova. IEEE, 2015. http://dx.doi.org/10.1109/oceans-genova.2015.7271359.
Pełny tekst źródłaZhou, Junwu, Hongchang He, Xiaolan Xie i Ke Xu. "Research on Multi-source Heterogeneous Ocean Data Integration System". W DSIT 2020: 2020 3rd International Conference on Data Science and Information Technology. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3414274.3414503.
Pełny tekst źródłaBagga, Pawandeep, Pradeep Shukla i Chandrajyoti Chitroda. "Optimizing Completion Through Real-Time High-Resolution Resistivity Imaging Tool for Fracture Mapping in Horizontal Wells". W Offshore Technology Conference Asia. OTC, 2024. http://dx.doi.org/10.4043/34858-ms.
Pełny tekst źródłaSato, Takumi, Kangsoo Kim, Masahiko Sasano, Akihiro Okamoto, Shogo Inaba, Satoshi Kondo, Hiroshi Matsumoto, Takashi Murashima, Toshifumi Fujiwara i Hiroyuki Osawa. "Sea Trials of Multiple Heterogenous Cruising AUVs and ASV With Basic Formation Control". W ASME 2023 42nd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/omae2023-103370.
Pełny tekst źródłaJing, Liu, i Yue Lin. "Research on data interaction of multi-source heterogeneous information in ocean strategy environment". W 2017 IEEE 2nd International Conference on Big Data Analysis (ICBDA). IEEE, 2017. http://dx.doi.org/10.1109/icbda.2017.8078827.
Pełny tekst źródłaMyshkin, Vyacheslav F., Valery A. Khan, Dmitriy A. Izhoykin, Aygul K. Orazymbetova, Nyrzhamal A. Ospanovа, Aliya N. Kargulova, Vadim V. Dudorov, Denis L. Gamov, Vladimir N. Lensky i Evgeniya S. Abramova. "Reduction of data processing error of heterogeneous system laser sensing". W XXIV International Symposium, Atmospheric and Ocean Optics, Atmospheric Physics, redaktorzy Oleg A. Romanovskii i Gennadii G. Matvienko. SPIE, 2018. http://dx.doi.org/10.1117/12.2506127.
Pełny tekst źródłaRaporty organizacyjne na temat "Heterogeneous oceanic data"
Sommer, Stefan, Sascha Flögel, Michael Walter i Frank Wenzhöfer. Autonomous Robotic Network to Resolve Coastal Oxygen Dynamics : Cruise No. AL547, 20.10. – 31.10.2020, Kiel – Kiel, ARCODYN. GEOMAR Helmholtz Centre for Ocean Research Kiel, 2022. http://dx.doi.org/10.3289/cr_al547.
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