Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications
Latest Publications

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Published By SPIE

9781510626775, 9781510626782

Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

Front Matter: Volume 11006

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications ◽

10.1117/12.2537937 ◽

2019 ◽

Keyword(s):

Matter Volume

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Improving unmanned aerial vehicle-based object detection via adversarial training: a (almost) free lunch to enjoy (Conference Presentation)

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications ◽

10.1117/12.2518835 ◽

2019 ◽

Author(s):

Zhenyu Wu ◽

Karthik Suresh ◽

Zhangyang Wang ◽

Priya Narayanan ◽

Heesung Kwon

Keyword(s):

Object Detection ◽

Unmanned Aerial Vehicle ◽

Free Lunch ◽

Aerial Vehicle ◽

Adversarial Training

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Deep HoriXons (DHX): a 3D virtual reality research campus for crowd-sourcing AI innovations in cooperative autonomy (Conference Presentation)

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications ◽

10.1117/12.2518316 ◽

2019 ◽

Author(s):

Rob Williams

Keyword(s):

Virtual Reality ◽

Crowd Sourcing

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Towards an intelligent tactical edge: an internet of battlefield things roadmap (Conference Presentation)

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications ◽

10.1117/12.2522648 ◽

2019 ◽

Author(s):

Tarek Abdelzaher ◽

Stephen Russell

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VoI for complex AI based solutions in coalition environments

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications ◽

10.1117/12.2519619 ◽

2019 ◽

Author(s):

Dinesh Verma ◽

Geeth R. de Mel ◽

Gavin Pearson

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On the machine learning for minimizing the negative influence in mobile cyber physical systems

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications ◽

10.1117/12.2519598 ◽

2019 ◽

Author(s):

Vijay Chaudhary ◽

Danda Rawat

Keyword(s):

Machine Learning ◽

Negative Influence ◽

Cyber Physical Systems ◽

Physical Systems

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Developing the sensitivity of LIME for better machine learning explanation

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications ◽

10.1117/12.2520149 ◽

2019 ◽

Author(s):

Eunjin Lee ◽

David Braines ◽

Mitchell Stiffler ◽

Adam Adam Hudler ◽

Daniel Harborne

Keyword(s):

Machine Learning

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Super resolution-assisted deep aerial vehicle detection

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications ◽

10.1117/12.2519045 ◽

2019 ◽

Cited By ~ 3

Author(s):

Syeda Nyma Ferdous ◽

Moktari Mostofa ◽

Nasser Nasrabadi

Keyword(s):

Super Resolution ◽

Vehicle Detection ◽

Aerial Vehicle

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Overview of machine learning (ML) based perception algorithms for unstructured and degraded visual environments

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications ◽

10.1117/12.2519029 ◽

2019 ◽

Cited By ~ 1

Author(s):

Priya Narayanan ◽

Zhenyu Wu ◽

Heesung Kwon ◽

Zhangyang Wang ◽

Raghuveer Rao

Keyword(s):

Machine Learning

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Reducing the cost of visual DL datasets

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications ◽

10.1117/12.2519114 ◽

2019 ◽

Author(s):

Philip R. Osteen ◽

Jason L. Owens ◽

Brian Kaukeinen

Keyword(s):

The Cost

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Artificial Intelligence and Machine Learning for Multi-Domain Operations ApplicationsLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By SPIE

Front Matter: Volume 11006

Improving unmanned aerial vehicle-based object detection via adversarial training: a (almost) free lunch to enjoy (Conference Presentation)

Deep HoriXons (DHX): a 3D virtual reality research campus for crowd-sourcing AI innovations in cooperative autonomy (Conference Presentation)

Towards an intelligent tactical edge: an internet of battlefield things roadmap (Conference Presentation)

VoI for complex AI based solutions in coalition environments

On the machine learning for minimizing the negative influence in mobile cyber physical systems

Developing the sensitivity of LIME for better machine learning explanation

Super resolution-assisted deep aerial vehicle detection

Overview of machine learning (ML) based perception algorithms for unstructured and degraded visual environments

Reducing the cost of visual DL datasets

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications
Latest Publications