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Books and Theses
- 2015
[b1]Mahesh Subedar:
Visual Quality with a Focus on 3D Blur Discrimination and Texture Granularity. Arizona State University, Tempe, USA, 2015
Journal Articles
- 2016
- [j1]Mahesh M. Subedar, Lina J. Karam
:
3D Blur Discrimination. ACM Trans. Appl. Percept. 13(3): 12:1-12:13 (2016)
Conference and Workshop Papers
- 2023
- [c15]Jun-Liang Lin, Ranganath Krishnan, Keyur Ruganathbhai Ranipa, Mahesh Subedar, Vrushabh Sanghavi, Meena Arunachalam, Omesh Tickoo, Ravishankar Iyer, Mahmut Taylan Kandemir:
Quantization for Bayesian Deep Learning: Low-Precision Characterization and Robustness. IISWC 2023: 180-192 - [c14]Charles Hong, Qijing Huang, Grace Dinh, Mahesh Subedar, Yakun Sophia Shao:
DOSA: Differentiable Model-Based One-Loop Search for DNN Accelerators. MICRO 2023: 209-224 - 2022
- [c13]Shashank Bujimalla, Mahesh Subedar, Omesh Tickoo:
Partially-Supervised Novel Object Captioning Using Context from Paired Data. BMVC 2022: 649 - [c12]Qijing Huang, Charles Hong, John Wawrzynek, Mahesh Subedar, Yakun Sophia Shao:
Learning A Continuous and Reconstructible Latent Space for Hardware Accelerator Design. ISPASS 2022: 277-287 - 2020
- [c11]Ranganath Krishnan, Mahesh Subedar, Omesh Tickoo:
Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes. AAAI 2020: 4477-4484 - 2019
- [c10]Mahesh Subedar, Ranganath Krishnan, Paulo Lopez-Meyer, Omesh Tickoo, Jonathan Huang:
Uncertainty aware audiovisual activity recognition using deep Bayesian variational inference. CVPR Workshops 2019: 103-108 - [c9]Mahesh Subedar, Ranganath Krishnan, Paulo Lopez-Meyer, Omesh Tickoo, Jonathan Huang:
Uncertainty-Aware Audiovisual Activity Recognition Using Deep Bayesian Variational Inference. ICCV 2019: 6300-6309 - [c8]Ranganath Krishnan, Mahesh Subedar, Omesh Tickoo:
Efficient Priors for Scalable Variational Inference in Bayesian Deep Neural Networks. ICCV Workshops 2019: 773-777 - 2017
- [c7]Nilesh A. Ahuja, Mahesh Subedar, Omesh Tickoo, Yeongseon Lee:
A Factorization Approach for Enabling Structure-from-Motion/SLAM Using Integer Arithmetic. ICCV Workshops 2017: 554-562 - 2015
- [c6]Mahesh M. Subedar, Lina J. Karam:
A subjective study and an objective metric to quantify the granularity level of textures. Human Vision and Electronic Imaging 2015: 93940G - [c5]Mahesh M. Subedar, Lina J. Karam:
A no reference texture granularity index and application to visual media compression. ICIP 2015: 760-764 - 2014
- [c4]Mahesh Subedar, Lina J. Karam:
Study of blur discrimination for 3D stereo viewing. SD&A 2014: 90110T - 2008
- [c3]Abhijit Sarkar, Mark D. Fairchild, Jorge E. Caviedes, Mahesh Subedar:
A Comparative Study of Color and Contrast Enhancement for Still Images and Consumer Video Applications. CIC 2008: 170-175 - 2004
- [c2]Mahesh Subedar, Lina J. Karam, Glen P. Abousleman:
An embedded scaling-based arbitrary shape region-of-interest coding method for JPEG2000. ICASSP (3) 2004: 681-684 - [c1]Mahesh Subedar, Lina J. Karam, Glen P. Abousleman:
JPEG2000-based shape adaptive algorithm for the efficient coding of multiple regions-of interest. ICIP 2004: 1293-1296
Informal and Other Publications
- 2024
- [i10]Athmanarayanan Lakshmi Narayanan, Ranganath Krishnan, Amrutha Machireddy, Mahesh Subedar:
Parameter-Efficient Active Learning for Foundational models. CoRR abs/2406.09296 (2024) - 2021
- [i9]Shashank Bujimalla, Mahesh Subedar, Omesh Tickoo:
Data augmentation to improve robustness of image captioning solutions. CoRR abs/2106.05437 (2021) - [i8]Shashank Bujimalla, Mahesh Subedar, Omesh Tickoo:
Partially-supervised novel object captioning leveraging context from paired data. CoRR abs/2109.05115 (2021) - [i7]Ranganath Krishnan, Alok Sinha, Nilesh A. Ahuja, Mahesh Subedar, Omesh Tickoo, Ravi Iyer:
Mitigating Sampling Bias and Improving Robustness in Active Learning. CoRR abs/2109.06321 (2021) - [i6]Ranganath Krishnan, Nilesh A. Ahuja, Alok Sinha, Mahesh Subedar, Omesh Tickoo, Ravi Iyer:
Improving Robustness and Efficiency in Active Learning with Contrastive Loss. CoRR abs/2109.06873 (2021) - 2020
- [i5]Shashank Bujimalla, Mahesh Subedar, Omesh Tickoo:
B-SCST: Bayesian Self-Critical Sequence Training for Image Captioning. CoRR abs/2004.02435 (2020) - 2019
- [i4]Ranganath Krishnan, Mahesh Subedar, Omesh Tickoo:
MOPED: Efficient priors for scalable variational inference in Bayesian deep neural networks. CoRR abs/1906.05323 (2019) - [i3]Mahesh Subedar, Nilesh A. Ahuja, Ranganath Krishnan, Ibrahima J. Ndiour, Omesh Tickoo:
Deep Probabilistic Models to Detect Data Poisoning Attacks. CoRR abs/1912.01206 (2019) - 2018
- [i2]Ranganath Krishnan, Mahesh Subedar, Omesh Tickoo:
BAR: Bayesian Activity Recognition using variational inference. CoRR abs/1811.03305 (2018) - [i1]Mahesh Subedar, Ranganath Krishnan, Paulo Lopez-Meyer, Omesh Tickoo, Jonathan Huang:
Uncertainty aware multimodal activity recognition with Bayesian inference. CoRR abs/1811.10811 (2018)
Coauthor Index
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