most citedTime Efficient Training of Progressive Generative Adversarial Network using Depthwise Separable Convolution and Super Resolution Generative Adversarial Network

3 citations · 4 across the 3 of their papers we have counts for

collaborators

3 papers

eess.IV2022★ 3 cited

Time Efficient Training of Progressive Generative Adversarial Network using Depthwise Separable Convolution and Super Resolution Generative Adversarial Network

Atharva Karwande, Pranesh Kulkarni, Tejas Kolhe +2

Generative Adversarial Networks have been employed successfully to generate high-resolution augmented images of size 1024^2. Although the augmented images generated are unprecedent…

physics.optics2022★ 1 cited

Single-shot multispectral quantitative phase imaging using deep neural network

Sunil Bhatt, Ankit Butola, Anand Kumar +5

Multi-spectral quantitative phase imaging (MS-QPI) is a cutting-edge label-free technique to determine the morphological changes, refractive index variations and spectroscopic info…

cs.CV2020

Art Style Classification with Self-Trained Ensemble of AutoEncoding Transformations

Akshay Joshi, Ankit Agrawal, Sushmita Nair

The artistic style of a painting is a rich descriptor that reveals both visual and deep intrinsic knowledge about how an artist uniquely portrays and expresses their creative visio…