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Kevin V Dicrispino

age ~48

from New Orleans, LA

Also known as:
  • Kevin Vincent Dicrispino
  • Kevin O
Phone and address:
2206 Killdeer St, New Orleans, LA 70122
5048129653

Kevin Dicrispino Phones & Addresses

  • 2206 Killdeer St, New Orleans, LA 70122 • 5048129653
  • 7169 Parkside Ct, New Orleans, LA 70127 • 5042428599
  • Harahan, LA
  • 274 Nicklaus Dr, Slidell, LA 70458 • 9856418890

Work

  • Company:
    Gcr inc.
    Feb 1, 2011
  • Position:
    Gis manager

Education

  • School / High School:
    Brother Martin High School

Skills

Gis • Cartography • Esri • Remote Sensing • Spatial Analysis • Arcgis • Arcmap • Analysis • Spatial Databases • Gps • Microsoft Sql Server • Arcinfo • Geomatics • Government • Data Mapping • Geography • Geodatabase • Arcsde • Arcgis Server • Data Analysis • Geoprocessing

Ranks

  • Certificate:
    Remote Sensing, Computer Cartography, and Gis

Industries

Information Technology And Services

Us Patents

  • Method And Apparatus For Non-Invasive Rapid Fungal Specie (Mold) Identification Having Hyperspectral Imagery

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  • US Patent:
    20080102487, May 1, 2008
  • Filed:
    Nov 1, 2006
  • Appl. No.:
    11/590747
  • Inventors:
    Haibo Yao - Slidell LA, US
    Zuzana Hruska - Covington LA, US
    Kevin Dicrispino - Harahan LA, US
    Robert L. Brown - Prairieville LA, US
    Thomas E. Cleveland - Mandeville LA, US
  • Assignee:
    Institute for Technology Development - Stennis Space Center MS
    USDA Southern Regional Research Center - Baton Rouge LA
  • International Classification:
    C40B 20/04
    G06F 19/00
    C12Q 1/04
  • US Classification:
    435 34, 702 19, 506 4
  • Abstract:
    In a method and apparatus for identifying and distinguishing fungal species, a hyperspectral imaging scanner is used to acquire hyperspectral image data for radiation obtained from a sample area in which at least one unknown fungal species is present. A computer compares the acquired hyperspectral image data with spectral signature data stored in a digital library, which includes spectral signature data for each one of a group of known fungal species, and identifies the fungal species, based on the result of such comparison. The spectral signature data stored in the digital library take into account, for each fungal species, spectral variations that can occur due to at least one of environmental and temporal influences. The computer comparison includes a pixel-by-pixel analysis of the degree of difference between acquired hyperspectral image data and the spectral signature data, so that a spatial distribution of identified fungal species can be determined for a sample area.

Resumes

Kevin Dicrispino Photo 1

Gis Manager

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Location:
New Orleans, LA
Industry:
Information Technology And Services
Work:
Gcr Inc.
Gis Manager

City of New Orleans Jun 2006 - Feb 2011
Contractor: Gis Analyst

Institute For Technology Development Apr 1999 - Jun 2006
Image Analyst Ii
Education:
Brother Martin High School
University of New Orleans
Bachelors, Bachelor of Arts, Geography
Skills:
Gis
Cartography
Esri
Remote Sensing
Spatial Analysis
Arcgis
Arcmap
Analysis
Spatial Databases
Gps
Microsoft Sql Server
Arcinfo
Geomatics
Government
Data Mapping
Geography
Geodatabase
Arcsde
Arcgis Server
Data Analysis
Geoprocessing
Certifications:
Remote Sensing, Computer Cartography, and Gis
Geographic Information Services Professional (Gis)

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