Nairit Barkataki

Size estimation of underground targets from GPR frequency spectra: A deep learning approach

By Nairit Barkataki / Leave a Comment / Research Papers

Abstract . GPR (Ground Penetrating Radar) is a robust and effective device for identifying underground artefacts. Construction companies and civil engineers should be aware of the sizes of rebars and pipelines before and during construction work for various reasons. Most

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Estimation of soil moisture from GPR data using Artificial Neural Networks

By Nairit Barkataki / Leave a Comment / Research Papers

Abtract

Soil moisture estimation is essential for understanding the water cycle and its impact on weather and climate. GPR based soil moisture estimation is non-invasive in nature and provides quicker results as compared to standard laboratory approaches. Deep learning algorithms

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A CNN model for predicting size of buried objects from GPR B-Scans

By Nairit Barkataki / Leave a Comment / Research Papers

Abstract . A convolutional neural networks (CNN) model for predicting size of buried objects from ground penetrating radar (GPR) B-Scans is proposed. As a pre-processing step, Sobel, Laplacian, Scharr, and Canny operators are used for edge detection of the hyperbolic

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Classification of Soil Types from GPR B-Scans using Deep Learning Techniques

By Nairit Barkataki / 2 Comments / Research Papers

Abstract . Traditional methods for classification of soil types are time consuming, invasive and expensive. A non-invasive method like ground penetrating radar (GPR) provides a suitable way to classify soil types based on its electromagnetic properties. Deep learning algorithms have

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