1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.LG2021
Orthogonal Features Based EEG Signals Denoising Using Fractional and Compressed One-Dimensional CNN AutoEncoder
Subham Nagar, Ahlad Kumar
This paper presents a fractional one-dimensional convolutional neural network (CNN) autoencoder for denoising the Electroencephalogram (EEG) signals which often get contaminated wi…
eess.IV2021★ 1 cited
Tchebichef Transform Domain-based Deep Learning Architecture for Image Super-resolution
Ahlad Kumar, Harsh Vardhan Singh
The recent outbreak of COVID-19 has motivated researchers to contribute in the area of medical imaging using artificial intelligence and deep learning. Super-resolution (SR), in th…
cs.LG2021
Orthogonal Features-based EEG Signal Denoising using Fractionally Compressed AutoEncoder
Subham Nagar, Ahlad Kumar, M. N. S. Swamy
A fractional-based compressed auto-encoder architecture has been introduced to solve the problem of denoising electroencephalogram (EEG) signals. The architecture makes use of frac…