Name: Convective Cell Tracking through Deep Learning based Computer Vision (en Inglés)
Price: 52.33 USD
Availability: InStock
Author: Ranganayakulu, S. V. ; Subrahmanyam, K. V. ; Niranjan, Akella
ISBN: 9786203194814

portada Convective Cell Tracking through Deep Learning based Computer Vision (en Inglés)

Formato

Libro Físico

Autor

S. V. Ranganayakulu

K. V. Subrahmanyam

Akella Niranjan

Editorial

LAP Lambert Academic Publishing

Idioma

Inglés

N° páginas

Encuadernación

Tapa Blanda

Dimensiones

22.9 x 15.2 x 0.5 cm

Peso

0.12 kg.

ISBN13

9786203194814

Categorías

Ingeniería electrónica

Convective Cell Tracking through Deep Learning based Computer Vision (en Inglés)

S. V. Ranganayakulu (Autor) · K. V. Subrahmanyam (Autor) · Akella Niranjan (Autor) · LAP Lambert Academic Publishing · Tapa Blanda

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Reseña del libro "Convective Cell Tracking through Deep Learning based Computer Vision (en Inglés)"

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.