Michael E Garris, Age 763106 N Stonebridge Dr, Norfolk, VA 23504

Michael Garris Phones & Addresses

3106 N Stonebridge Dr, Norfolk, VA 23504 (804) 389-9731

3142 Stonebridge Dr, Norfolk, VA 23504 (757) 333-3060

Virginia Beach, VA

Laurel, MD

3106 N Stonebridge Dr, Norfolk, VA 23504

Work

Company: Tscm security services Aug 2012 Position: Physical security specialist

Education

School / High School: Defense Security Service Academy 2008 Specialities: Certificate in Security Professional Educational Curriculum

Mentions for Michael E Garris

Career records & work history

License Records

Michael J Garris

Licenses:
License #: 178 - Expired
Category: Well Driller
Issued Date: Jun 28, 2007
Effective Date: Jan 5, 2009
Expiration Date: Dec 31, 2008
Type: Natural Resource Ground Water Tech

Michael Garris resumes & CV records

Resumes

Michael Garris Photo 29

Director Atac Norfolk

Location:
Norfolk, VA
Industry:
Government Administration
Work:
Navsup Fleet Logistics Center Norfolk
Director Atac Norfolk
Michael Garris Photo 30

Michael Garris

Michael Garris Photo 31

Michael Garris

Michael Garris Photo 32

Michael Garris - Upper Marlboro, MD

Work:
TSCM Security Services Aug 2012 to 2000
Physical Security Specialist
Facchina Global Services - La Plata, MD Jun 2010 to Apr 2012
Construction Site Security Manager (CSSM)
Facchina Global Services - LaPlata, Md May 2008 to Jun 2010
Security Specialist/Manager
Inter-Con Security Systems, Incorporated - Alexandria, VA Aug 2005 to May 2008
Armed Uniformed Protection Officer
Caddo Parrish Sheriff Office - Shreveport, LA Aug 2002 to Aug 2005
Sheriff Deputy
National Institutes of Health (NIH) - Bethesda, MD Jun 2000 to Jul 2001
Security Guard Administrator
Education:
Defense Security Service Academy 2008 to 2010
Certificate in Security Professional Educational Curriculum
Everest College - Arlington, VA 2007 to 2007
Diploma in Homeland Security Specialist
Louisiana Regional Police Academy - Shreveport, LA 2002 to 2002
Sheriff Deputy in Police Officer Standards of Training(POST)

Publications & IP owners

Us Patents

Standard Calibration Target For Contactless Fingerprint Scanners

US Patent:
2013007, Mar 21, 2013
Filed:
Sep 21, 2012
Appl. No.:
13/623898
Inventors:
Shahram Orandi - Potomac MD, US
Fred Byers - Knoxville MD, US
Stephen Harvey - Gaithersburg MD, US
Michael D. Garris - Boyds MD, US
Stephen S. Wood - Chevy Chase MD, US
John M. Libert - Rockville MD, US
Jin Chu Wu - Frederick MD, US
International Classification:
G06K 9/78
US Classification:
382124
Abstract:
A contactless, three-dimensional fingerprint scanner apparatus, method, and system are described. The contactless fingerprint scanner can provide either, or both, topographical contrast of three-dimensional fingerprint features and optical contrast of a three-dimensional fingerprint surface. Data captured from scanning of a target with known geometric features mimicking fingerprint features can be examined as images or surface plots and analyzed for fidelity against the known target feature specifications to evaluate or validate device capture performance as well as interoperability. The target can be used by scanner vendors and designers to validate their devices, as well as to perform type certification.

Object/Anti-Object Neural Network Segmentation

US Patent:
5245672, Sep 14, 1993
Filed:
Mar 9, 1992
Appl. No.:
7/847490
Inventors:
Charles L. Wilson - Darnestown MD
Michael D. Garris - Gaithersburg MD
Robert A. Wilkinson - Hyattstown MD
Assignee:
The United States of America as represented by the Secretary of Commerce - Washington DC
International Classification:
G06K 900
US Classification:
382 9
Abstract:
The system of the present invention applies self-organizing and/or supervd learning network methods to the problem of segmentation. The segmenter receives a visual field, implemented as a sliding window and distinguishes occurrences of complete characters from occurrences of parts of neighboring characters. Images of isolated whole characters are true objects and the opposite of true objects are anti-objects, centered on the space between two characters. The window is moved across a line of text producing a sequence of images and the segmentation system distinguishes true objects from anti-objects. Frames classified as anti-objects demarcate character boundaries, and frames classified as true objects represent detected character images. The system of the present invention may be a feedforward adaption using a symmetric triggering network. Inputs to the network are applied directly to the separate associative memories of the network.

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