L. Boominathan, M. Maniparambil, H. Gupta, R. Baburajan, and K. Mitra, “Phase retrieval for fourier ptychography under varying amount of measurements,” arXiv preprint arXiv:1805.03593, 2018
L. Boominathan, M. Maniparambil, H. Gupta, R. Baburajan, and K. Mitra, “Phase retrieval for fourier ptychography under varying amount of measurements,” arXiv preprint arXiv:1805.03593, 2018
@inproceedings{Maniparambil_2022_BMVC, author = {Mayug Maniparambil and Kevin McGuinness and Noel O Connor}, title = {BaseTransformers: Attention over base data-points for One Shot Learning}, booktitle = {33rd British Machine Vision Conference 2022, {BMVC} 2022, London, UK, November 21-24, 2022}, publisher = {{BMVA} Press}, year = {2022}, url = {https://bmvc2022.mpi-inf.mpg.de/0482.pdf} }
Poster on Phase retrieval for Fourier Ptychography under varying amount of measurements presented at (Computational Cameras and Displays) CCD workshop, CVPR 2018
Presented a poster ‘Denoising High Density Mouse Brain Images using Deep Generative Models’ at Society for Neuroscience Conference 2017 , Washington D.C.
“Large Scale Topological Analysis of Cranial Bleeds” paper and open source dataset to be submitted to the Lancet (as of Oct 2020).
1 Poster presented at machine learning track of European Congress of Radiology (ECR) 2020 on building bleed classification algorithms robust to CT acquisition artifacts.
Published:
A generative model(GAN) based approach to inpaint serial two photon tomography images of mice brain. In collaboration with Dr. Pavel Osten’s Lab, Cold Spring Harbor Laboratory.
Recommended citation: M. Maniparambil, A. Vadathya, K. Venkataraju, KK. Mitra, P. Osten, “Denoising High Density Gene Expression in Whole Mouse Brain Images” arXiv preprint arXiv:1805.03593, 2017 http://academicpages.github.io/files/deep_fpm_paper.pdf