Isbn: 9786203194814 - convective cell tracking through deep learning based computer vision: python-based algorithm for identification & tracking of convective cells using doppler weather radar reflectivity images (9 resultados)

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  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2020

    6203194816 / 9786203194814

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    Editorial: LAP LAMBERT Academic Publishing, 2020

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  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2020

    6203194816 / 9786203194814

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    Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK

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  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Dez 2020, 2020

    6203194816 / 9786203194814

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    Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The present study developed an autonomous algorithm for the Convective cell Identification and TRAcking (CITRA) using DWR reflectivity images. The CITRA algorithm is implemented in Python using Deep learning technique of Neural Networks. Optical Character Recognition is used in the present study through 'Tesseract' which is an unsupervised Neural Network module based on LSTM which analyses the input dimensional pixel array/image and outputs high-level strings. The algorithm runs through the DWR reflectivity image pixel values and recognizes the intensities of the pixels (>=30 dB) and segregates convective cells along with other estimated cell properties such as centroid of the storm, the area covered, distance and direction from the radar centre. The performance of CITRA algorithm was tested on different convective storms and it could successfully identify and track them along with other physical properties of the convective cells. Further, we have demonstrated the potential application of CITRA algorithm on the evolution of convective cells detected within the radar range. Presently, CITRA algorithm takes only reflectivity images as a single input parameter. 76 pp. Englisch.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2020

    6203194816 / 9786203194814

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The present study developed an autonomous algorithm for the Convective cell Identification and TRAcking (CITRA) using DWR reflectivity images. The CITRA algorithm is implemented in Python using Deep learning technique of Neural Networks. Optical Character Recognition is used in the present study through 'Tesseract' which is an unsupervised Neural Network module based on LSTM which analyses the input dimensional pixel array/image and outputs high-level strings. The algorithm runs through the DWR reflectivity image pixel values and recognizes the intensities of the pixels (>=30 dB) and segregates convective cells along with other estimated cell properties such as centroid of the storm, the area covered, distance and direction from the radar centre. The performance of CITRA algorithm was tested on different convective storms and it could successfully identify and track them along with other physical properties of the convective cells. Further, we have demonstrated the potential application of CITRA algorithm on the evolution of convective cells detected within the radar range. Presently, CITRA algorithm takes only reflectivity images as a single input parameter.…

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    Editorial: LAP LAMBERT Academic Publishing, 2020

    6203194816 / 9786203194814

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    Librería: moluna, Greven, Alemaniamoluna

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    EUR 34,25

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    Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ranganayakulu S. V.S. V. Ranganayakulu is currently working as Dean (R&D), in Guru Nanak Institutions Technical Campus(Autonomous) and holds M.Sc (Physics) in Electronics as specialization, M.Phil (Physics) in the area of Liquid Crys.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Dez 2020, 2020

    6203194816 / 9786203194814

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    Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

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    Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The present study developed an autonomous algorithm for the Convective cell Identification and TRAcking (CITRA) using DWR reflectivity images. The CITRA algorithm is implemented in Python using Deep learning technique of Neural Networks. Optical Character Recognition is used in the present study through 'Tesseract' which is an unsupervised Neural Network module based on LSTM which analyses the input dimensional pixel array/image and outputs high-level strings. The algorithm runs through the DWR reflectivity image pixel values and recognizes the intensities of the pixels (>=30 dB) and segregates convective cells along with other estimated cell properties such as centroid of the storm, the area covered, distance and direction from the radar centre. The performance of CITRA algorithm was tested on different convective storms and it could successfully identify and track them along with other physical properties of the convective cells. Further, we have demonstrated the potential application of CITRA algorithm on the evolution of convective cells detected within the radar range. Presently, CITRA algorithm takes only reflectivity images as a single input parameter.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 76 pp. Englisch.…