Dr. Kevin L. Priddy
Branch Technical Advisor at
SPIE Involvement:
Fellow status | Conference Program Committee | Conference Co-Chair | Conference Chair | Author | Editor | Instructor
Area of Expertise:
Wide Area Motion Imaging , Pattern Recognition , Machine Learning , Layered Sensing , Artificial Neural Networks , Systems Engineering
Profile Summary

Dr. Kevin L. Priddy, is Technical Advisor, Sensor Exploitation Applications Branch, Sensors Directorate, Air Force Research Laboratory, Wright-Patterson Air Force Base, Ohio. The directorate specializes in developing science and technology for superior Air Force systems in the areas of intelligence, surveillance, reconnaissance, precision engagement and electronic warfare. He directs the technical efforts of the Sensor Exploitation Applications Branch in performing research and transitioning technology to meet Air Force needs.


AWARDS AND HONORS

2004, Jacobs Sverdrup, Senior Technical Award
2007, Air Force Research Laboratory Senior Leadership Award
2008, Sensors Directorate Senior Leadership Award
2008, Sensors Directorate Director’s Cup Team Award: Project AngelFire
2009, Air Force Research Laboratory, Commander’s Cup Team Award: Project AngelFire
2009, Air Force STEM Award Exploratory or Advanced Technology Development Team: Angel Fire Team
2010, Sensors Directorate, Director’s Cup, Senior Individual
2011, Air Force Research Laboratory, Commander’s Cup, Senior Individual
2011, Air Force Achievement Medal

BOOKS

“Artificial Neural Networks: An Introduction,” Kevin L. Priddy and Paul E. Keller, SPIE-International Society for Optical Engineering, October 2005, ISBN-13:9780819459879

PATENTS

United States Patent 5,850,625; “Sensor Fusion Apparatus and Method,” December 15, 1998
United States Patent 6,889,165; “Application Specific Intelligent Microsensor,” May 3, 2005.
United States Patent 6,995,655 “Method of simultaneously reading multiple radio frequency tags, RF tags, and RF reader,” February 7, 2006.

PROFESSIONAL MEMBERSHIPS AND ASSOCIATIONS
Senior Member IEEE
Member SPIE
Tau Beta Pi
Eta Kappa Nu

PROFESSIONAL CERTIFICATIONS
SPRDE-Science and Technology Manager, Level III
SPRDE-Systems Engineer, Level III
Publications (36)

PROCEEDINGS ARTICLE | May 20, 2015
Proc. SPIE. 9464, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VI
KEYWORDS: Image compression, Detection and tracking algorithms, Data modeling, Image processing, Video, Distortion, Computer programming, JPEG2000, Image quality, Video compression

PROCEEDINGS ARTICLE | May 20, 2015
Proc. SPIE. 9464, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VI
KEYWORDS: Image compression, Image processing, Video, Computer programming, Video surveillance, JPEG2000, Transform theory, Video compression, Quantization, Algorithm development

PROCEEDINGS ARTICLE | May 3, 2012
Proc. SPIE. 8391, Automatic Target Recognition XXII
KEYWORDS: Image compression, Detection and tracking algorithms, Visualization, Sensors, Data storage, Image processing, Pattern recognition, 3D modeling, Algorithm development, 3D image processing

Showing 5 of 36 publications
Conference Committee Involvement (18)
Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VI
20 April 2015 | Baltimore, Maryland, United States
Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR V
5 May 2014 | Baltimore, Maryland, United States
Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IV
29 April 2013 | Baltimore, Maryland, United States
Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR III
23 April 2012 | Baltimore, Maryland, United States
Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR II
26 April 2011 | Orlando, Florida, United States
Showing 5 of 18 published special sections
Course Instructor
SC166: Fundamentals of Artificial Neural Networks
The course starts with the history of research into biological neural networks used for unsolved problems in information processing. The technology of physiologically motivated information processing to solve engineering problems had advanced. Neural networks for finding patterns in data have progressed out of the laboratory and into products. This course provides the background to understand and apply this technology for recognizing patterns in data.
SC360: Advanced Neural Networks
Neural networks have been around for over forty years. This course presents many examples of artificial neural networks and provides the attendee with a thorough understanding of the most popular neural networks such as back propagation trained feed-forward neural networks, self-organizing feature maps, adaptive resonance theory (ART), generalized linear and hybrid neural networks. The attendee is given the theoretical background needed to understand why one network or combination of networks works on a given problem but may not be a good choice for others. The instructor introduces the latest algorithms and their applications to many engineering problems.
SC791: A Practical Course in Neural Networks
This course provides attendees with a basic working knowledge of artificial neural network design. The course concentrates on various types of neural networks and where they can be used to solve common classification problems. Many practical and useful examples are included throughout the course.
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