Detection of non-technical losses using advanced metering infrastructure and deep recurrent neural networks S Chatterjee, V Archana, K Suresh, R Saha, R Gupta, F Doshi 2017 IEEE International Conference on Environment and Electrical Engineering …, 2017 | 28 | 2017 |
Automated sperm morpshology testing using artificial intelligence P Thirumalaraju, CL Bormann, M Kanakasabapathy, F Doshi, I Souter, ... Fertility and sterility 110 (4), e432, 2018 | 23 | 2018 |
Adaptive adversarial neural networks for the analysis of lossy and domain-shifted datasets of medical images MK Kanakasabapathy, P Thirumalaraju, H Kandula, F Doshi, ... Nature biomedical engineering 5 (6), 571-585, 2021 | 11 | 2021 |
Organizational motifs of cortical responses to objects emerge in topographic projections of deep neural networks F Doshi, T Konkle Journal of Vision 21 (9), 2226-2226, 2021 | 4 | 2021 |
Machine learning predictions of irradiation embrittlement in reactor pressure vessel steels Y Liu, H Wu, T Mayeshiba, B Afflerbach, R Jacobs, J Perry, J George, ... npj Computational Materials 8 (1), 85, 2022 | 2 | 2022 |
Visual object topographic motifs emerge from self-organization of a unified representational space FR Doshi, T Konkle BioRxiv, 2022.09. 06.506403, 2022 | 2 | 2022 |
Human-Like Judgments of Stability Emerge from Purely Perceptual Features: Evidence from Supervised and Unsupervised Deep Neural Networks C Conwell, F Doshi, GA Alvarez | 2 | 2019 |
Human-like signatures of contour integration in deep neural networks F Doshi, T Konkle, G Alvarez Journal of Vision 22 (14), 4222-4222, 2022 | | 2022 |
Using Deep Convolutional Neural Networks to Examine the Role of Representational Similarity in Visual Working Memory F Doshi, H Pailian, GA Alvarez Journal of Vision 20 (11), 149-149, 2020 | | 2020 |
Shared Representations of Stability in Humans, Supervised, & Unsupervised Neural Networks C Conwell, F Doshi, GA Alvarez | | 2019 |
Thread Organization and Intra-Thread Datasharing (TOITD) FR Doshi, RH Pooniwala, G Vijayalakshmi | | 2014 |