Tailored for real-world: a whole slide image classification system validated on uncurated multi-site data emulating the prospective pathology workload JD Ianni, RE Soans, S Sankarapandian, RV Chamarthi, D Ayyagari, ... Scientific reports 10 (1), 3217, 2020 | 87 | 2020 |
A pathology deep learning system capable of triage of melanoma specimens utilizing dermatopathologist consensus as ground truth S Sankarapandian, S Kohn, V Spurrier, S Grullon, RE Soans, ... Proceedings of the IEEE/CVF International Conference on Computer Vision, 629-638, 2021 | 20 | 2021 |
A novel 1d-convolution accelerator for low-power real-time cnn processing on the edge J Sanchez, N Soltani, R Chamarthi, A Sawant, H Tabkhi 2018 IEEE High Performance extreme Computing Conference (HPEC), 1-8, 2018 | 11 | 2018 |
A reconfigurable streaming processor for real-time low-power execution of convolutional neural networks at the edge J Sanchez, N Soltani, P Kulkarni, RV Chamarthi, H Tabkhi Edge Computing–EDGE 2018: Second International Conference, Held as Part of …, 2018 | 5 | 2018 |
Augmenting the Pathology Lab: An Intelligent Whole Slide Image Classification System for the Real World JD Ianni, RE Soans, S Sankarapandian, RV Chamarthi, D Ayyagari, ... arXiv preprint arXiv:1909.11212, 2019 | 2 | 2019 |
Algorithmic Optimization of First Convolution Layer in CNNs for Hardware Accelerator Design RV Chamarthi The University of North Carolina at Charlotte, 2019 | | 2019 |