Charles B. Delahunt

According to our database, Charles B. Delahunt authored at least 19 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Driving down Poisson error can offset classification error in clinical tasks.

Charles B. Delahunt, Courosh Mehanian, Matthew P. Horning

CoRR, 2024

2023

How Good Are Synthetic Medical Images? An Empirical Study with Lung Ultrasound.

Menghan Yu, Sourabh Kulhare, Courosh Mehanian, Charles B. Delahunt, Daniel E. Shea, Zohreh Laverriere, Ishan Shah, Matthew P. Horning

Proceedings of the Simulation and Synthesis in Medical Imaging, 2023

Deep Learning Video Classification of Lung Ultrasound Features Associated with Pneumonia.

Daniel E. Shea, Sourabh Kulhare, Rachel Millin, Zohreh Laverriere, Courosh Mehanian, Charles B. Delahunt, Dipayan Banik, Xinliang Zheng, Meihua Zhu, Ye Ji, Travis Ostbye, Martha-Marie S. Mehanian, Atinuke Uwajeh, Adeseye M. Akinsete, Fen Wang, Matthew P. Horning

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

PySINDy: A comprehensive Python package for robust sparse system identification.

Alan A. Kaptanoglu, Brian de Silva, Urban Fasel, Kadierdan Kaheman, Andy Goldschmidt, Jared Callaham, Charles B. Delahunt, Zachary Nicolaou, Kathleen P. Champion, Jean-Christophe Loiseau, J. Nathan Kutz, Steven L. Brunton

J. Open Source Softw., 2022

Use case-focused metrics to evaluate machine learning for diseases involving parasite loads.

Charles B. Delahunt, Noni Gachuhi, Matthew P. Horning

CoRR, 2022

A Toolkit for Data-Driven Discovery of Governing Equations in High-Noise Regimes.

Charles B. Delahunt, J. Nathan Kutz

IEEE Access, 2022

2021

PySINDy: A comprehensive Python package for robust sparse system identification.

Alan A. Kaptanoglu, Brian M. de Silva, Urban Fasel, Kadierdan Kaheman, Jared L. Callaham, Charles B. Delahunt, Kathleen P. Champion, Jean-Christophe Loiseau, J. Nathan Kutz, Steven L. Brunton

CoRR, 2021

2020

Predicting United States policy outcomes with Random Forests.

Shawn K. McGuire, Charles B. Delahunt

CoRR, 2020

Algorithms to predict moisture content of grain using relative humidity time-series.

Charles B. Delahunt, Wenbo Wang, Simon Ghionea, Andrew Miller, Austin Chan, Anjali Sehrawat, Courosh Mehanian, Michael Friend

Proceedings of the IEEE Global Humanitarian Technology Conference, 2020

2019

Putting a bug in ML: The moth olfactory network learns to read MNIST.

Charles B. Delahunt, J. Nathan Kutz

Neural Networks, 2019

Fully-automated patient-level malaria assessment on field-prepared thin blood film microscopy images, including Supplementary Information.

Charles B. Delahunt, Mayoore S. Jaiswal, Matthew P. Horning, Samantha Janko, Clay M. Thompson, Sourabh Kulhare, Liming Hu, Travis Ostbye, Grace Yun, Roman Gebrehiwot, Benjamin K. Wilson, Earl Long, Stephane Proux, Dionicia Gamboa, Peter Chiodini, Jane Carter, Mehul Dhorda, David Isaboke, Bernhards Ogutu, Wellington Oyibo, Elizabeth Villasis, Kyaw Myo Tun, Christine Bachman, David Bell, Courosh Mehanian

CoRR, 2019

Money on the Table: Statistical information ignored by Softmax can improve classifier accuracy.

Charles B. Delahunt, Courosh Mehanian, J. Nathan Kutz

CoRR, 2019

Fully-automated patient-level malaria assessment on field-prepared thin blood film microscopy images.

Charles B. Delahunt, Roman Gebrehiwot, Benjamin K. Wilson, Earl Long, Stephane Proux, Dionicia Gamboa, Peter Chiodini, Jane Carter, Mehul Dhorda, David Isaboke, Bernhards Ogutu, Mayoore S. Jaiswal, Wellington Oyibo, Elizabeth Villasis, Kyaw Myo Tun, Christine Bachman, David Bell, Courosh Mehanian, Matthew P. Horning, Samantha Janko, Clay M. Thompson, Sourabh Kulhare, Liming Hu, Travis Ostbye, Grace Yun

Proceedings of the IEEE Global Humanitarian Technology Conference, 2019

2018

Biological Mechanisms for Learning: A Computational Model of Olfactory Learning in the Manduca sexta Moth, With Applications to Neural Nets.

Charles B. Delahunt, Jeffrey A. Riffell, J. Nathan Kutz

Frontiers Comput. Neurosci., 2018

Insect cyborgs: Biological feature generators improve machine learning accuracy on limited data.

Charles B. Delahunt, J. Nathan Kutz

CoRR, 2018

A moth brain learns to read MNIST.

Charles B. Delahunt, J. Nathan Kutz

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Computer-Automated Malaria Diagnosis and Quantitation Using Convolutional Neural Networks.

Courosh Mehanian, Mayoore S. Jaiswal, Charles B. Delahunt, Clay Thompson, Matthew P. Horning, Liming Hu, Shawn K. McGuire, Travis Ostbye, Martha Mehanian, Benjamin K. Wilson, Cary R. Champlin, Earl Long, Stephane Proux, Dionicia Gamboa, Peter Chiodini, Jane Carter, Mehul Dhorda, David Isaboke, Bernhards Ogutu, Wellington Oyibo, Elizabeth Villasis, Kyaw Myo Tun, Christine Bachman, David Bell

Proceedings of the 2017 IEEE International Conference on Computer Vision Workshops, 2017

2015

Automated microscopy and machine learning for expert-level malaria field diagnosis.

Charles B. Delahunt, Courosh Mehanian, Liming Hu, Shawn K. McGuire, Cary R. Champlin, Matthew P. Horning, Benjamin K. Wilson, Clay M. Thompson

Proceedings of the 2015 IEEE Global Humanitarian Technology Conference, 2015

2012

Design goals for a system for enhancing AAC with personalized video.

Katie O'Leary, Charles B. Delahunt, Patricia Dowden, Ivan Darmansya, Jiaqi Heng, Eve A. Riskin, Richard E. Ladner, Jacob O. Wobbrock

Proceedings of the 14th International ACM SIGACCESS Conference on Computers and Accessibility, 2012