Uncertainty-aware audiovisual activity recognition using deep bayesian variational inference M Subedar, R Krishnan, PL Meyer, O Tickoo, J Huang Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 63 | 2019 |
Specifying weight priors in bayesian deep neural networks with empirical bayes R Krishnan, M Subedar, O Tickoo Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 4477-4484, 2020 | 44 | 2020 |
Devices and methods for accurately identifying objects in a vehicle's environment N Ahuja, I Ndiour, JF Leon, DG Gutierrez, R Krishnan, M Subedar, ... US Patent 11,586,854, 2023 | 33 | 2023 |
Increased depth perception with sharpness enhancement for stereo video MM Subedar, LJ Karam Stereoscopic Displays and Applications XXI 7524, 450-457, 2010 | 33 | 2010 |
BAR: Bayesian activity recognition using variational inference R Krishnan, M Subedar, O Tickoo arXiv preprint arXiv:1811.03305, 2018 | 27 | 2018 |
Joint enhancement of lightness, color and contrast of images and video A Sarkar, JE Caviedes, M Subedar US Patent 8,477,247, 2013 | 24 | 2013 |
Bayesian-torch: Bayesian neural network layers for uncertainty estimation R Krishnan, P Esposito, M Subedar Jan, 2022 | 22 | 2022 |
Deep probabilistic models to detect data poisoning attacks M Subedar, N Ahuja, R Krishnan, IJ Ndiour, O Tickoo arXiv preprint arXiv:1912.01206, 2019 | 17 | 2019 |
Method and apparatus for blocking artifact detection and measurement in block-coded video JE Caviedes, MM Subedar, WT Tang, R Ferzli US Patent 7,606,423, 2009 | 17 | 2009 |
Frame rate conversion using motion estimation and compensation M Subedar, JE Caviedes US Patent 8,724,022, 2014 | 15 | 2014 |
An embedded scaling-based arbitrary shape region-of-interest coding method for JPEG2000 MM Subedar, LJ Karam, GP Abousleman 2004 IEEE International Conference on Acoustics, Speech, and Signal …, 2004 | 15 | 2004 |
Learning a continuous and reconstructible latent space for hardware accelerator design Q Huang, C Hong, J Wawrzynek, M Subedar, YS Shao 2022 IEEE International Symposium on Performance Analysis of Systems and …, 2022 | 13 | 2022 |
Methods and apparatus to obtain well-calibrated uncertainty in Deep Neural Networks R Krishnan, O Tickoo, N Ahuja, I Ndiour, M Subedar US Patent App. 17/133,072, 2021 | 12 | 2021 |
Post-incident management for autonomous vehicles DG Aguirre, O Florez, JZ ESQUIVEL, M Subedar, JF Leon, R Chierichetti, ... US Patent 10,726,577, 2020 | 12 | 2020 |
Efficient priors for scalable variational inference in Bayesian deep neural networks R Krishnan, M Subedar, O Tickoo Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 12 | 2019 |
Subjective and objective visual quality assessment in the context of stereoscopic 3D-TV M Barkowsky, K Brunnström, T Ebrahimi, L Karam, P Lebreton, ... 3D-TV System With Depth-Image-Based Rendering: Architectures, Techniques and …, 2013 | 12 | 2013 |
The effect of texture granularity on texture synthesis quality SA Golestaneh, MM Subedar, LJ Karam Applications of Digital Image Processing XXXVIII 9599, 356-361, 2015 | 11 | 2015 |
A no reference texture granularity index and application to visual media compression MM Subedar, LJ Karam 2015 IEEE International Conference on Image Processing (ICIP), 760-764, 2015 | 9 | 2015 |
Joint enhancement of lightness, color and contrast of images and video A Sarkar, JE Caviedes, M Subedar US Patent 9,053,523, 2015 | 9 | 2015 |
Detecting video format information in a sequence of video pictures JE Caviedes, MM Subedar US Patent 7,982,805, 2011 | 9 | 2011 |