Charles B. Delahunt

Orcid: 0000-0003-4860-8069

According to our database1, Charles B. Delahunt authored at least 19 papers between 2012 and 2024.

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Bibliography

2024
Driving down Poisson error can offset classification error in clinical tasks.
CoRR, 2024

2023
How Good Are Synthetic Medical Images? An Empirical Study with Lung Ultrasound.
Proceedings of the Simulation and Synthesis in Medical Imaging, 2023

Deep Learning Video Classification of Lung Ultrasound Features Associated with Pneumonia.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
PySINDy: A comprehensive Python package for robust sparse system identification.
J. Open Source Softw., 2022

Use case-focused metrics to evaluate machine learning for diseases involving parasite loads.
CoRR, 2022

A Toolkit for Data-Driven Discovery of Governing Equations in High-Noise Regimes.
IEEE Access, 2022

2021
PySINDy: A comprehensive Python package for robust sparse system identification.
CoRR, 2021

2020
Predicting United States policy outcomes with Random Forests.
CoRR, 2020

Algorithms to predict moisture content of grain using relative humidity time-series.
Proceedings of the IEEE Global Humanitarian Technology Conference, 2020

2019
Putting a bug in ML: The moth olfactory network learns to read MNIST.
Neural Networks, 2019

Fully-automated patient-level malaria assessment on field-prepared thin blood film microscopy images, including Supplementary Information.
CoRR, 2019

Money on the Table: Statistical information ignored by Softmax can improve classifier accuracy.
CoRR, 2019


2018
Biological Mechanisms for Learning: A Computational Model of Olfactory Learning in the Manduca sexta Moth, With Applications to Neural Nets.
Frontiers Comput. Neurosci., 2018

Insect cyborgs: Biological feature generators improve machine learning accuracy on limited data.
CoRR, 2018

A moth brain learns to read MNIST.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017

2015
Automated microscopy and machine learning for expert-level malaria field diagnosis.
Proceedings of the 2015 IEEE Global Humanitarian Technology Conference, 2015

2012
Design goals for a system for enhancing AAC with personalized video.
Proceedings of the 14th International ACM SIGACCESS Conference on Computers and Accessibility, 2012


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