Ahlad Kumar
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View article: Orthogonal Transform based Generative Adversarial Network for Image Dehazing
Orthogonal Transform based Generative Adversarial Network for Image Dehazing Open
Image dehazing has become one of the crucial preprocessing steps for any computer vision task. Most of the dehazing methods try to estimate the transmission map along with the atmospheric light to get the dehazed image in the image domain.…
View article: Deep Learning Architecture Based Approach For 2D-Simulation of Microwave Plasma Interaction
Deep Learning Architecture Based Approach For 2D-Simulation of Microwave Plasma Interaction Open
This paper presents a convolutional neural network (CNN)-based deep learning model, inspired from UNet with series of encoder and decoder units with skip connections, for the simulation of microwave-plasma interaction. The microwave propag…
View article: Orthogonal Features Based EEG Signals Denoising Using Fractional and Compressed One-Dimensional CNN Autoencoder
Orthogonal Features Based EEG Signals Denoising Using Fractional and Compressed One-Dimensional CNN Autoencoder Open
This paper presents a fractional one-dimensional convolutional neural network (CNN) autoencoder for denoising the Electroencephalogram (EEG) signals which often get contaminated with noise during the recording process, mostly due to muscle…
View article: Orthogonal Features Based EEG Signals Denoising Using Fractional and Compressed One-Dimensional CNN AutoEncoder
Orthogonal Features Based EEG Signals Denoising Using Fractional and Compressed One-Dimensional CNN AutoEncoder Open
This paper presents a fractional one-dimensional convolutional neural network (CNN) autoencoder for denoising the Electroencephalogram (EEG) signals which often get contaminated with noise during the recording process, mostly due to muscle…
View article: Tchebichef Transform Domain-based Deep Learning Architecture for Image Super-resolution
Tchebichef Transform Domain-based Deep Learning Architecture for Image Super-resolution Open
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 the past few years, has produced remarkable results using dee…
View article: A Framework for Image Denoising Using First and Second Order Fractional Overlapping Group Sparsity (HF-OLGS) Regularizer
A Framework for Image Denoising Using First and Second Order Fractional Overlapping Group Sparsity (HF-OLGS) Regularizer Open
Denoising images subjected to Gaussian and Poisson noise has attracted attention in many areas of image processing. This paper introduces an image denoising framework using higher order fractional overlapping group sparsity prior to sparse…
View article: Complementary metal‐oxide semiconductor implementation of digital filters for signal processing applications
Complementary metal‐oxide semiconductor implementation of digital filters for signal processing applications Open
Realisations of filters in signal processing using interconnects as delay elements have been presented. Normally, these filters are implemented using switched capacitor technique. However, in digital realisations of these filters, flip flo…