Object detection neural network improves Fourier ptychography reconstruction F Ströhl, S Jadhav, BS Ahluwalia, K Agarwal, DK Prasad Optics Express 28 (25), 37199-37208, 2020 | 12 | 2020 |
Single-shot multispectral quantitative phase imaging of biological samples using deep learning S Bhatt, A Butola, A Kumar, P Thapa, A Joshi, S Jadhav, N Singh, ... Applied Optics 62 (15), 3989-3999, 2023 | 6 | 2023 |
Artefact removal in ground truth deficient fluctuations-based nanoscopy images using deep learning S Jadhav, S Acuña, IS Opstad, B Singh Ahluwalia, K Agarwal, DK Prasad Biomedical Optics Express 12 (1), 191-210, 2020 | 5 | 2020 |
Multi-Plateau Ensemble for Endoscopic Artefact Segmentation and Detection S Jadhav, U Bamba, A Chavan, R Tiwari, A Raj 2nd International Workshop and Challenge on Computer Vision in Endoscopy …, 2020 | 4 | 2020 |
Deep learning-based denoising of acoustic images generated with point contact method S Jadhav, R Kuchibhotla, K Agarwal, A Habib, DK Prasad Journal of Nondestructive Evaluation, Diagnostics and Prognostics of …, 2023 | 2 | 2023 |
Reconstructing 3D shape from 3D ThunderSTORM Point Clouds S Jadhav, S Majhi, AS Chowdhury, DK Prasad, K Agarwal Focus on Microscopy 2023, Porto, Portugal, 2023 | | 2023 |
MiShape: 3D Shape Modelling of Mitochondria in Microscopy AR Punnakkal, SS Jadhav, A Horsch, K Agarwal, DK Prasad arXiv preprint arXiv:2303.01546, 2023 | | 2023 |
Deep learning in frequency space enables sample-independent parameter estimation in Fourier ptychographic microscopy S Jadhav, F Ströhl Novel Techniques in Microscopy, NF2C. 5, 2021 | | 2021 |
Supplementary notes: Artefact removal in ground truth deficient fluctuations-based nanoscopy images using deep learning S JADHAV, S ACUÑA, I OPSTAD, BS AHLUWALIA, K AGARWAL, ... | | |