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2020 – today
- 2022
[c9]Aditya Ranganath, Omar DeGuchy, Fabian Santiago, Mukesh Singhal, Roummel F. Marcia:
Recurrent Nerual Imaging: An Evolutionary Approach for Mixed Possion-Gaussian Image Denoising. ICMLA 2022: 484-489- 2021
- [c8]Aditya Ranganath, Omar DeGuchy, Mukesh Singhal, Roummel F. Marcia:
Multi-Stage Gaussian Noise Reduction with Recurrent Neural Networks. ACSCC 2021: 135-139 - [c7]Aditya Ranganath, Omar DeGuchy, Mukesh Singhal, Roummel F. Marcia:
Second-Order Trust-Region Optimization for Data-Limited Inference. EUSIPCO 2021: 2059-2063 - 2020
- [b1]Omar DeGuchy:
Large-Scale Optimization and Deep Learning Techniques for Data-Driven Signal Processing. University of California, Merced, USA, 2020 - [c6]Mario Banuelos, Omar DeGuchy, Suzanne Sindi, Roummel F. Marcia:
Related Inference: A Supervised Learning Approach to Detect Signal Variation in Genome Data. EUSIPCO 2020: 1215-1219 - [c5]Jacqueline Alvarez, Omar DeGuchy, Roummel F. Marcia:
Image Classification in Synthetic Aperture Radar Using Reconstruction from Learned Inverse Scattering. IGARSS 2020: 2867-2870 - [c4]Michael Fernando Mendez Jimenez, Omar DeGuchy, Roummel F. Marcia:
Deep Convolutional Autoencoders for Deblurring and Denoising Low-Resolution Images. ISITA 2020: 549-553
2010 – 2019
- 2019
- [c3]Omar DeGuchy, Fabian Santiago, Mario Banuelos, Roummel F. Marcia:
Deep Neural Networks for Low-resolution Photon-limited Imaging. ICASSP 2019: 3247-3251 - 2018
- [j1]Omar DeGuchy, Jennifer B. Erway, Roummel F. Marcia
:
Compact representation of the full Broyden class of quasi-Newton updates. Numer. Linear Algebra Appl. 25(5) (2018) - [c2]Jacob Rafati, Omar DeGuchy, Roummel F. Marcia:
Trust-Region Minimization Algorithm for Training Responses (TRMinATR): The Rise of Machine Learning Techniques. EUSIPCO 2018: 2015-2019 - 2017
- [c1]Omar DeGuchy, Lasith Adhikari, Arnold D. Kim, Roummel F. Marcia:
Photon-Limited fluorescence lifetime imaging microscopy signal recovery with known bounds. CAMSAP 2017: 1-5
Coauthor Index
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