Scott S. Howard

According to our database, Scott S. Howard authored at least 9 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

DAPS++: Rethinking Diffusion Inverse Problems with Decoupled Posterior Annealing.

Hao Chen, Renzheng Zhang, Scott S. Howard

CoRR, November, 2025

Zero-Shot Denoising for Fluorescence Lifetime Imaging Microscopy with Intensity-Guided Learning.

Hao Chen, Julian Najera, Dagmawit Geresu, Meenal Datta, Cody J. Smith, Scott S. Howard

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2025

2023

Improving fluorescence lifetime imaging microscopy phasor accuracy using convolutional neural networks.

Varun Mannam, Jacob Brandt, Cody J. Smith, Xiaotong Yuan, Scott S. Howard

Frontiers Bioinform., May, 2023

2022

Low dosage 3D volume fluorescence microscopy imaging using compressive sensing.

Varun Mannam, Jacob Brandt, Cody J. Smith, Scott S. Howard

CoRR, 2022

2021

Convolutional Neural Network Denoising in Fluorescence Lifetime Imaging Microscopy (FLIM).

Varun Mannam, Yide Zhang, Xiaotong Yuan, Takashi Hato, Pierre C. Dagher, Evan L. Nichols, Cody J. Smith, Kenneth W. Dunn, Scott S. Howard

CoRR, 2021

Deep learning-based super-resolution fluorescence microscopy on small datasets.

Varun Mannam, Yide Zhang, Xiaotong Yuan, Scott S. Howard

CoRR, 2021

2020

Packet Compressed Sensing Imaging (PCSI): Robust Image Transmission over Noisy Channels.

Scott S. Howard, Grant Barthelmes, Cara Ravasio, Lisa Huang, Benjamin Poag, Varun Mannam

CoRR, 2020

Machine learning for faster and smarter fluorescence lifetime imaging microscopy.

Varun Mannam, Yide Zhang, Xiaotong Yuan, Cara Ravasio, Scott S. Howard

CoRR, 2020

2019

A Poisson-Gaussian Denoising Dataset With Real Fluorescence Microscopy Images.

Yide Zhang, Yinhao Zhu, Evan L. Nichols, Qingfei Wang, Siyuan Zhang, Cody J. Smith, Scott S. Howard

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019