Manager, Technical Support, DIRECTV Set Top Box Team at Samsung Electronics America
Location:
Orange County, California Area
Industry:
Consumer Electronics
Work:
Samsung Electronics America - Long Beach, CA since Oct 2012
Manager, Technical Support, DIRECTV Set Top Box Team
Samsung Information Systems America - Long Beach, CA Sep 2007 - Sep 2012
Senior Engineer
Olympus America Feb 2000 - Sep 2007
Field Service Engineer
Buehler Ltd 1995 - Feb 2000
Field Service Engineer
U.S. Air Force - CA, NE, TX, FL, CO, South Korea Dec 1982 - Jan 1993
Space Systems Electronics Technician, Pavements Specialist
Education:
Colorado State University Global Campus 2012 - 2014
Master of Science (MS), International Business
Community College of the Air Force
Associates in Science, Electronic Engineering Technology
Thomas Edison State College
Bachelor of Science, Business Adminitration
Yuba College
Associates in Science, Math, Science & Enginering
Honor & Awards:
Air Force Achievement Medal (five), National Defense Service Medal, Iraq Campain Service Medal
Partner / Software Engineer At Sourceflux Mobile Development
Co-founder / Software Engineer at Sourceflux Mobile Development
Location:
Greater Los Angeles Area
Industry:
Computer Software
Work:
Sourceflux Mobile Development since Mar 2010
Co-founder / Software Engineer
Newtron Inc. - Nederland, TX Jul 2004 - Sep 2012
Network Administrator
Joseph landry Jan 1995 - Sep 2012
Consultant
Gymnastics Rockland, MA Jun 2004 to Jan 2014 TeacherTwenty Four Seven Inc. Los Angeles, CA Nov 2013 to Nov 2013 Brand AmbassadorStarbucks Coffee Hingham, MA 2011 to 2012 BaristaDirectBuy of Boston South Rockland, MA 2009 to 2011 SalesJ.L. Painting Abington, MA 2004 to 2011 Assistant to OperationsSouth Shore Racquet & Fitness Rockland, MA 2004 to 2009 Customer Service / Facility Operations
Education:
University of Massachusetts Dartmouth Dartmouth, MA BusinessMassasoit Community College Brockton, MA Business, Theatre
Senior Buyer at Accellent, Inc., Firefighter, First Lieutenant at West Brookfield Fire Department
Location:
Brimfield, Massachusetts
Industry:
Medical Devices
Work:
Accellent, Inc. since Oct 1983
Senior Buyer
West Brookfield Fire Department - West Brookfield, MA since Oct 2009
Firefighter, First Lieutenant
West Brookfield Fire Department - West Brookfield, MA Aug 1995 - Oct 2009
Firefighter
Education:
Fisher College 1983 - 1988
Associate's degree, Business Administration and Management, General
Paul M. Ingram - Dallas TX, US Joseph C. Landry - Dallas TX, US John J. Coogan - Bedford TX, US Paul D. Shocklee - Plano TX, US
Assignee:
Raytheon Company - Waltham MA
International Classification:
G06G 7/48 G06F 7/60 G06F 17/10
US Classification:
703 6, 703 2
Abstract:
In accordance with the present disclosure, a computer implemented system and method predicts the performance for a remote material identification process under real conditions and uncertainties. The method and system transforms data representing measured reflectance values for candidate materials based on environmental conditions, and uncertainties regarding the environmental conditions and/or calibration of sensors measuring radiance values into the performance predictions for a material identification process operating under those conditions and uncertainties. The performance predictions can be communicated to a designer of, for example, a multi-angle material identification system for use in selecting and setting up the system, or communicated to a consumer of images captured by the material identification system for use in interpreting results of application of the material identification process to real imagery acquired with remote sensors.
Paul M. Ingram - Dallas TX, US Joseph C. Landry - Dallas TX, US John J. Coogan - Bedford TX, US Paul D. Shocklee - Plano TX, US
Assignee:
Raytheon Company - Waltham MA
International Classification:
G06F 17/18
US Classification:
702181, 252582
Abstract:
In one example of a method for remote identifying a non-Lambertian target material, a spectral signature for a target is determined from each of at least two different sets of imagery acquired at different angles, and compared to a predicted signature for a candidate material for each of the at least two different angles. The predicted signatures take into account the known anisotropy of reflectance, and thus also radiance, of the candidate material.
In-Scene Determination Of Aerosol Parameters From Imagery
A computer implemented method and apparatus estimate background reflectance, aerosol type and visibility within a multispectral imagery using the measured spectral radiance of one or more calibration targets of known reflectance and the measured radiance of the background of the target. The computer implemented method and apparatus uses predefined aerosol types, characterized by a plurality of known parameters, and the known reflectance of the one or more calibration targets, to select an aerosol that best matches the measured radiances.
Joseph C. Landry - Dallas TX, US John J. Coogan - Bedford TX, US Paul D. Shocklee - Plano TX, US
International Classification:
G06F 17/18
US Classification:
702181
Abstract:
In one example of a method for remote identifying a non-Lambertian target material, a spectral signature for a target is determined from each of at least two different sets of imagery acquired at different angles, and compared to a predicted signature for a candidate material for each of the at least two different angles. The predicted signatures take into account the known anisotropy of reflectance, and thus also radiance, of the candidate material.
Determining Minimum Region For Finding Planar Surfaces
- Waltham MA, US Jody D. Verret - Rockwall TX, US Joseph C. Landry - Dallas TX, US
International Classification:
G06T 17/05 G06T 7/11
Abstract:
Systems, devices, methods, and computer-readable media for determining planarity in a 3D data set are provided. A method can include receiving or retrieving three-dimensional (3D) data of a geographical region, dividing the 3D data into first contiguous regions of specified first geographical dimensions, determining, for each first contiguous region of the first contiguous regions, respective measures of variation, identifying, based on the respective measures of variation, a search radius, dividing the 3D data into respective second contiguous or overlapping regions with dimensions the size of the identified search radius, and determining, based on the identified search radius, a planarity of each of the respective second contiguous or overlapping regions.
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