Mr. John F. Gilmore Profile

John F. Gilmore

at General Dynamics Mission Systems

SPIE Involvement:

Author

Proceedings Article | 1 September 2004 Paper

UAV team behaviors in operational scenarios

John Gilmore, Joseph Garbarino

Proceedings Volume 5417, (2004) https://doi.org/10.1117/12.541398

KEYWORDS: Unmanned aerial vehicles, Ultraviolet radiation, Sensors, Relays, Control systems, Vehicle control, Environmental sensing, Radar, Reconnaissance, Data communications

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Proceedings Article | 16 August 2001 Paper

Force detection and identification system

Michael Pagels, John Gilmore

Proceedings Volume 4380, (2001) https://doi.org/10.1117/12.436970

KEYWORDS: System identification, Image processing, Image fusion, Image registration, Systems modeling, Computing systems, Sensors, Detection and tracking algorithms, Synthetic aperture radar

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The Force Detection and Identification System (FDIS) provides an operationally capable near-real-time platform appropriate for the evaluation of state-of-the-art imagery exploitation components and architectural design principles on scalable platforms. FDIS's architectural features include: a highly modular component design allowing rapid component interchange, multiple intercomponent datapaths which support both fine- and course-grained parallelism, an infrastructure which supports heterogeneous computing on a range of high-performance computing platforms, and conceptual decoupling between image processing and non-image processing components while supporting multi-level evidence fusion. While none of these features are individually unique, when combined they represent a state-of-the-art imagery exploitation system. FDIS has demonstrated probability of detection and false alarm rates consistent with other SAR-based exploitation systems. FDIS, however, requires fewer computing resources, supports rapid insertion of new or changed components to support emerging technologies with an ease not encountered in legacy systems, and is smoothly scalable. In addition to exploiting these novel architectural features, FDIS includes a new multi-dimensional evidence fusion component; Force Estimation (FE). Previous exploitation systems have demonstrated the positive impact on probability of detection and false alarm rates obtained by clustering vehicle detections into groups. FE, however, as a fusion component extends evidence accrual beyond simple spatial characteristics. Based on a fast multipole algorithm, FE accrues probabilistic evidence on models of military unit compositions. Fused evidence includes vehicle classifications, cultural and terrain features, and electronic emission features. FE's algorithmic speed allows operation in near-real-time without requiring excessive computational resources. FE has demonstrated improved force detection results over a wide range of operational conditions.

Proceedings Article | 27 March 2001 Paper

Multimedia agent monitoring and assessment system

John Gilmore, Michael Pagels, Justin Palk

Proceedings Volume 4384, (2001) https://doi.org/10.1117/12.421078

KEYWORDS: Information technology, Visualization, Databases, Internet, Data modeling, Televisions, Computing systems, Human-machine interfaces, Multimedia, Video

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Proceedings Article | 27 March 2001 Paper

Project X: competitive intelligence data mining and analysis

John Gilmore, Michael Pagels, Justin Palk

Proceedings Volume 4384, (2001) https://doi.org/10.1117/12.421081

KEYWORDS: Internet, Java, Data mining, Standards development, Databases, Video, Computing systems, Televisions, Information security, Network security

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Proceedings Article | 27 March 2001 Paper

Asymmetric threat data mining and knowledge discovery

John Gilmore, Michael Pagels, Justin Palk

Proceedings Volume 4384, (2001) https://doi.org/10.1117/12.421076

KEYWORDS: Taxonomy, Internet, Data mining, Knowledge discovery, Video, Televisions, Databases, Profiling, Satellites, Mining

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Proceedings Article | 22 March 2001 Paper

CHOP STIX: an exploitation metasystem

Michael Pagels, John Gilmore

Proceedings Volume 4385, (2001) https://doi.org/10.1117/12.421105

KEYWORDS: Computing systems, Telecommunications, Sensors, Java, Objectives, Operating systems, Image transmission, Image storage, Computer simulations, Synthetic aperture radar

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Synthetic aperture radar (SAR), electro-optical (EO) imagery, and motion-target indicators (MTI) are sensors utilized in prime surveillance/reconnaissance systems. Each sensor system can generate substantial volumes of data requiring vast computational resources to support exploitation, the problem is only aggravated in systems which support multiple sensor evidence fusion components. The dynamic nature of military operational settings often makes it difficult to efficiently apply the computational resources necessary for successful exploitation. Current limited research suggests that dynamic, scalable and heterogeneous computer systems may be an avenue to develop successful exploitation systems of the future. Existing research and development into systems of this type has not explicitly addressed their use for tactical imagery exploitation system. The Collaborative Heterogeneous Operations Prototype (CHOP) as part of DARPAs Scalable Tactical Imagery eXploitation (STIX) program conducted a review of existing state of the art commercial and non-commercial middleware and metasystem technology as applicable to STIX's technical objectives (the architectural characterization of a multiple source exploitation system appropriate for use in a dynamic military operational setting). The results of that review resulted in the design and development of a heterogeneous metasystem demonstrating state of the art near real time exploitation technology in the solution of multiple source imagery exploitation problems. The system was evaluated against measures of effectiveness and measures of performance applied to previously built and fielded imagery exploitation systems; its performance was consistent with those systems. CHOP STIX, however, offered automatic dynamic system reconfiguration to maximize system performance in an environment of changing mission requirements, sensor selection, data load, and computational resource availability. These characteristics made CHOP STIX appropriate for use in a wider range of operational settings than existing systems.

Proceedings Article | 18 September 1998 Paper

Airborne video surveillance

John Gilmore, David Garren

Proceedings Volume 3371, (1998) https://doi.org/10.1117/12.323823

KEYWORDS: Video, Video surveillance, Sensors, Unmanned aerial vehicles, Image registration, Telecommunications, Infrared sensors, Infrared imaging, Surveillance, Image sensors

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Proceedings Article | 26 August 1998 Paper

Battlespace exploitation visualization

John Gilmore, David Garren

Proceedings Volume 3395, (1998) https://doi.org/10.1117/12.319445

KEYWORDS: Visualization, Data modeling, Sensors, Visual analytics, Visual process modeling, Imaging systems, Image segmentation, Image visualization, Image processing, Human-machine interfaces

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Proceedings Article | 26 June 1997 Paper

Battlespace exploitation vision

John Gilmore, Ray Johnson

Proceedings Volume 3080, (1997) https://doi.org/10.1117/12.277172

KEYWORDS: Automatic target recognition, Synthetic aperture radar, Sensors, Target detection, Image processing, Target recognition, Radar, Image analysis, Electro optical modeling, Electro optics

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Proceedings Article | 10 June 1997 Paper

Semiautomated IMINT processing baseline system

John Gilmore, Larry Williams

Proceedings Volume 3066, (1997) https://doi.org/10.1117/12.276112

KEYWORDS: Image analysis, Target detection, Automatic target recognition, Synthetic aperture radar, Target recognition, Image processing, Data modeling, Sensors, Imaging systems, Human-computer interaction

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Proceedings Article | 30 June 1995 Paper

Unmanned guided vehicle system

John Gilmore, Harold Forbes, Kevin Payne, Khalid Elibiary

Proceedings Volume 2463, (1995) https://doi.org/10.1117/12.212746

KEYWORDS: Roads, Image segmentation, Image processing, Image processing algorithms and systems, Image enhancement, Navigation systems, Visualization, Image classification, Databases, Prototyping

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Proceedings Article | 16 September 1992 Paper

Neural network system for traffic flow management

John Gilmore, Khalid Elibiary, L. E. Rickard Petersson

Proceedings Volume 1709, (1992) https://doi.org/10.1117/12.140035

KEYWORDS: Control systems, Neural networks, Roads, Neurons, Signals intelligence, Data modeling, Artificial neural networks, Device simulation, Silicon, Information operations

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Proceedings Article | 1 February 1992 Paper

Object recognition using neural networks and high-order perspective-invariant relational descriptions

Kenyon Miller, John Gilmore

Proceedings Volume 1607, (1992) https://doi.org/10.1117/12.57098

KEYWORDS: Neural networks, Robot vision, Evolutionary algorithms, Image segmentation, Machine vision, Computer vision technology, Object recognition, Detection and tracking algorithms, Visual process modeling, Binary data

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SPIE Journal Paper | 1 May 1991

Knowledge-based target recognition system evolution

John Gilmore

OE, Vol. 30, Issue 05, (May 1991) https://doi.org/10.1117/12.10.1117/12.55829

KEYWORDS: Automatic target recognition, Image processing, Image segmentation, Target recognition, Detection and tracking algorithms, Evolutionary algorithms, Image processing algorithms and systems, Algorithm development, Sensors, Target detection

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Proceedings Article | 1 January 1990 Paper

Target detection in a neural-network environment

John Gilmore, Andrew Czuchry

Proceedings Volume 1293, (1990) https://doi.org/10.1117/12.21061

KEYWORDS: Target detection, Environmental sensing, Target recognition, Neural networks, Automatic target recognition, System integration, Analytical research, Infrared imaging, Infrared radiation, Databases

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