Mai H. Nguyen

Orcid: 0000-0002-1444-648X

According to our database1, Mai H. Nguyen authored at least 32 papers between 1993 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
Multimodal Wildland Fire Smoke Detection.
Remote. Sens., 2023

Prescribed Fire Modeling using Knowledge-Guided Machine Learning for Land Management.
CoRR, 2023

Developing a Best Practices Training Program in Cyberinfrastructure-Enabled Machine Learning Research.
Proceedings of the Practice and Experience in Advanced Research Computing, 2023

Voyager - An Innovative Computational Resource for Artificial Intelligence & Machine Learning Applications in Science and Engineering.
Proceedings of the Practice and Experience in Advanced Research Computing, 2023

Ensemble Based Learning for Automated Safety Labeling of Prescribed Fires.
Proceedings of the Computational Science - ICCS 2023, 2023

Visualization and Labeling of Terrestrial LiDAR Data for Three-Dimensional Fuel Classification.
Proceedings of the 19th IEEE International Conference on e-Science, 2023

2022
FIgLib & SmokeyNet: Dataset and Deep Learning Model for Real-Time Wildland Fire Smoke Detection.
Remote. Sens., 2022

Effects of data and entity ablation on multitask learning models for biomedical entity recognition.
J. Biomed. Informatics, 2022

Multimodal Wildland Fire Smoke Detection.
CoRR, 2022

2021
Generalization in Cardiac Image Segmentation.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2019
PEnBayes: A Multi-Layered Ensemble Approach for Learning Bayesian Network Structure from Big Data.
Sensors, 2019

Ten simple rules for writing and sharing computational analyses in Jupyter Notebooks.
PLoS Comput. Biol., 2019

Cardiac MRI Image Segmentation for Left Ventricle and Right Ventricle using Deep Learning.
CoRR, 2019

Understanding a Rapidly Expanding Refugee Camp Using Convolutional Neural Networks and Satellite Imagery.
Proceedings of the 15th International Conference on eScience, 2019

Scaling Deep Learning-Based Analysis of High-Resolution Satellite Imagery with Distributed Processing.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018
Ten Simple Rules for Reproducible Research in Jupyter Notebooks.
CoRR, 2018

Left Ventricle Segmentation and Volume Estimation on Cardiac MRI using Deep Learning.
CoRR, 2018

Scalable Detection of Rural Schools in Africa Using Convolutional Neural Networks and Satellite Imagery.
Proceedings of the 2018 IEEE/ACM International Conference on Utility and Cloud Computing Companion, 2018

Analytics Pipeline for Left Ventricle Segmentation and Volume Estimation on Cardiac MRI Using Deep Learning.
Proceedings of the 14th IEEE International Conference on e-Science, 2018

Land Cover Classification at the Wildland Urban Interface using High-Resolution Satellite Imagery and Deep Learning.
Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017
Modular Resource Centric Learning for Workflow Performance Prediction.
CoRR, 2017

An Unsupervised Deep Learning Approach for Satellite Image Analysis with Applications in Demographic Analysis.
Proceedings of the 13th IEEE International Conference on e-Science, 2017

Automated scalable detection of location-specific Santa Ana conditions from weather data using unsupervised learning.
Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

2016
Integrated Machine Learning in the Kepler Scientific Workflow System.
Proceedings of the International Conference on Computational Science 2016, 2016

A scalable approach for location-specific detection of Santa Ana conditions.
Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

Determining feature extractors for unsupervised learning on satellite images.
Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

2015
Towards an Integrated Cyberinfrastructure for Scalable Data-driven Monitoring, Dynamic Prediction and Resilience of Wildfires.
Proceedings of the International Conference on Computational Science, 2015

Big data provenance: Challenges, state of the art and opportunities.
Proceedings of the 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA, October 29, 2015

2014
A Scalable Data Science Workflow Approach for Big Data Bayesian Network Learning.
Proceedings of the 1st IEEE/ACM International Symposium on Big Data Computing, 2014

1997
Tau Net A neural network for modeling temporal variability.
Neurocomputing, 1997

1994
A Connectionist Approach to Rate Adaptation.
SIGART Bull., 1994

1993
Dynamic rate adaptation.
Artif. Intell. Rev., 1993


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