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Exploration of Pipelines from the use of GPR Data by Neural Network

2019; Volume: 8; Issue: 2S11 Linguagem: Inglês

10.35940/ijrte.b1470.0982s1119

2277-3878

Kode Rajiv, Basaveswara Booba, Ramesh Chandra, Varun Ganapathi, Booba Rao, G. Ramesh Chandra, G. Samuel Varaprasada Raju,

Geophysical Methods and Applications

Noticing about the buried pipes is a important issue, In many regions of the world. In spite of the fact that several techniques are there. This literature is used to find out the underground pipes automatically that provides accuracy execution is underway. Which gave amazing results Achieved by the deep learning of the different discoveries found in this article offer a pipeline to detect anti-personnel pipes Adaptive Neural Networks ( applied to the Ground Penetrating Radar (GPR). The proposed algorithm is suitable to recognize if the scanning format has been received. The acquisition of GPR has a track of anti-personnel pipes. The validity of the said system is made on a real GPR receipt, although systematic training can be done to have relied upon data generated by achievements. Based on the results 95% of the accuracy of detection got achieved without testing acquisition of pipes.