J. T. Turner

According to our database, J. T. Turner authored at least 13 papers between 2014 and 2024.

Collaborative distances:

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

2024

Counterfactual-Based Synthetic Case Generation.

Anik Sen, Mallika Mainali, Christopher B. Rauch, Ursula Addison, Michael W. Floyd, Prateek Goel, Justin Karneeb, Ray Kulhanek, Othalia Larue, David H. Ménager, Matthew Molineaux, J. T. Turner, Rosina O. Weber

Proceedings of the Case-Based Reasoning Research and Development, 2024

Aligning to Human Decision-Makers in Military Medical Triage.

Matthew Molineaux, Rosina O. Weber, Michael W. Floyd, David H. Ménager, Othalia Larue, Ursula Addison, Ray Kulhanek, Noah Reifsnyder, Christopher B. Rauch, Mallika Mainali, Anik Sen, Prateek Goel, Justin Karneeb, J. T. Turner, John Meyer

Proceedings of the Case-Based Reasoning Research and Development, 2024

Algorithmic Decision-Making in Difficult Scenarios.

Christopher B. Rauch, Ursula Addison, Michael W. Floyd, Prateek Goel, Justin Karneeb, Ray Kulhanek, Othalia Larue, David H. Ménager, Mallika Mainali, Matthew Molineaux, Adam Pease, Anik Sen, J. T. Turner, Rosina Weber

Proceedings of the AAAI 2024 Spring Symposium Series, 2024

2019

NOD-CC: A Hybrid CBR-CNN Architecture for Novel Object Discovery.

J. T. Turner, Michael W. Floyd, Kalyan Moy Gupta, Tim Oates

Proceedings of the Case-Based Reasoning Research and Development, 2019

2018

Novel Object Discovery Using Case-Based Reasoning and Convolutional Neural Networks.

J. T. Turner, Michael W. Floyd, Kalyan Moy Gupta, David W. Aha

Proceedings of the Case-Based Reasoning Research and Development, 2018

2017

Using Deep Learning to Automate Feature Modeling in Learning by Observation.

Michael W. Floyd, J. T. Turner, David W. Aha

Proceedings of the Thirtieth International Florida Artificial Intelligence Research Society Conference, 2017

Using Deep Learning to Automate Feature Modeling in Learning by Observation: A Preliminary Study.

Michael W. Floyd, J. T. Turner, David W. Aha

Proceedings of the 2017 AAAI Spring Symposia, 2017

2016

Keypoint Density-based Region Proposal for Fine-Grained Object Detection and Classification using Regions with Convolutional Neural Network Features.

J. T. Turner, Kalyan Moy Gupta, Brendan Morris, David W. Aha

CoRR, 2016

SPARCNN: Spatially related convolutional neural networks.

J. T. Turner, Kalyan Moy Gupta, David W. Aha

Proceedings of the 2016 IEEE Applied Imagery Pattern Recognition Workshop, 2016

Keypoint density-based region proposal for fine-grained object detection using regions with convolutional neural network features.

J. T. Turner, Kalyan Moy Gupta, David W. Aha

Proceedings of the 2016 IEEE Applied Imagery Pattern Recognition Workshop, 2016

2015

Convolutional Architecture Exploration for Action Recognition and Image Classification.

J. T. Turner, David W. Aha, Leslie Smith, Kalyan Moy Gupta

CoRR, 2015

2014

Comparing Raw Data and Feature Extraction for Seizure Detection with Deep Learning Methods.

Adam Page, J. T. Turner, Tinoosh Mohsenin, Tim Oates

Proceedings of the Twenty-Seventh International Florida Artificial Intelligence Research Society Conference, 2014

Deep Belief Networks Used on High Resolution Multichannel Electroencephalography Data for Seizure Detection.

J. T. Turner, Adam Page, Tinoosh Mohsenin, Tim Oates

Proceedings of the 2014 AAAI Spring Symposia, 2014