14 citations · 40 across the 6 of their papers we have counts for
6 papers
Stacked autoencoders based machine learning for noise reduction and signal reconstruction in geophysical data
Debjani Bhowick, Deepak K. Gupta, Saumen Maiti +1
Autoencoders are neural network formulations where the input and output of the network are identical and the goal is to identify the hidden representation in the provided datasets.…
Structural, Ferroelectric, Magnetic and Magnetoelectric Response in Multiferroic (1-x)Bi(Ni1/2Ti1/2)O3-PbTiO3/xNi0.6Zn0.4Fe2O4 Particulate Composites
Rishikesh Pandey, Uma Shankar, Sher Singh Meena +1
Multiferroic particulate composites have been fabricated by taking the morphotropic phase boundary composition of ferroelectric phase Bi(Ni1/2Ti1/2)O3-PbTiO3 and magnetic phase (Ni…
Deep Autoassociative Neural Networks for Noise Reduction in Seismic data
Debjani Bhowmick, Deepak K. Gupta, Saumen Maiti +1
Machine learning is currently a trending topic in various science and engineering disciplines, and the field of geophysics is no exception. With the advent of powerful computers, i…
Velocity-Porosity Supermodel: A Deep Neural Networks based concept
Debjani Bhowmick, Deepak K. Gupta, Saumen Maiti +1
Rock physics models (RPMs) are used to estimate the elastic properties (e.g. velocity, moduli) from the rock properties (e.g. porosity, lithology, fluid saturation). However, the r…
Investigation of Crystal Structure of SrLa(FeTi)O6 and BaLa(FeTi)O6 Perovskites by Rietveld Refinement
Uma Shankar, Puneet Kumar Agarwal, Rishikesh Pandey +1
The structures of the recently reported ordered perovskites SrLa(FeTi)O6 and BaLa(FeTi)O6 have been revisited using Rietveld analysis of the powder x-ray diffraction data. Our stud…
Absence of Tetragonal Distortion in (1-x)SrTiO3-xBi(Zn1/2Ti1/2)O3 Solid Solution
Rishikesh Pandey, Ravi Kiran Pillutla, Uma Shankar +1
We have carried out powder x-ray diffraction and dielectric studies on the lead free solid solution (1-x)SrTiO3-xBi(Zn1/2Ti1/2)O3 ((1-x)ST-xBZT) with x=0.05, 0.10, 0.15, 0.20, 0.30…