most citedEM based Framework for Single-shot Compressive Holography

10 citations · 13 across the 6 of their papers we have counts for

collaborators

6 papers

physics.optics2020

Geometric Solution of Image Degradation by Diffraction in Lensless Sensing and Microscopy

Sanjeev Kumar, Manjunatha Mahadevappa, Pranab Kumar Dutta

This paper proposes a non-computational method of counteracting the effect of image degradation introduced by the diffraction phenomenon in lensless microscopy. All the optical ima…

eess.IV2020

A semi-analytic reconstruction method for Diffuse Optical Tomography

Tapan Das, P. K. Dutta

The Diffuse Optical Tomography (DOT) has received considerable attention in the recent years in the field of biomedical imaging and disease detection. However, imaging through high…

physics.optics2020★ 2 cited

Lensless in-line holographic microscopy with light source of low spatio-temporal coherence

Sanjeev Kumar, Manjunatha Mahadevappa, Pranab Kumar Dutta

Lensless microscopy with coherent or partially coherent light sources is a well known imaging technique, commonly referred as digital in-line holographic microscopy. In the establi…

eess.IV2020★ 10 cited

EM based Framework for Single-shot Compressive Holography

Sanjeev Kumar, Manjunatha Mahadevappa, Pranab Kumar Dutta

Lensless in-line holography is a simple, portable, and cost-effective method of imaging especially for the biomedical microscopy applications. We propose a multiplicative gradient…

physics.optics2020★ 1 cited

Photonic crystal fiber for high resolution lensless in-line holographic microscopy

Sanjeev Kumar, Manjunatha Mahadevappa, Pranab K. Dutta

We propose to use high numerical aperture single mode optical fibers like photonic crystal fiber for lensless in-line holographic microscopy. Highly divergent beam helps to overcom…

cs.CV2015

Faster method for Deep Belief Network based Object classification using DWT

Saurabh Sihag, Pranab Kumar Dutta

A Deep Belief Network (DBN) requires large, multiple hidden layers with high number of hidden units to learn good features from the raw pixels of large images. This implies more tr…