The performance of KIMS in image recognition tasks

Celestine A. Ntuen; Eui H. Park; Young H. Park; Jung H. Kim; Kwang H. Sohn

doi:10.1016/0360-8352(90)90114-2

The performance of KIMS in image recognition tasks

Celestine A. Ntuen, Eui H. Park, Young H. Park, Jung H. Kim, Kwang H. Sohn

Department of Electrical and Electronic Engineering

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

KIMS is an acronym for a Knowledge-Based Image Management System developed in the Robotics and Artificial Intelligence Laboratory (RAIL) at North Carolina A&T State University. KIMS model architecture consists of rules which are developed through statistical experimentation with thresholding and quality control chart algorithms. The control architecture of KIMS is driven by the pattern of these rules. KIMS can analyze features of an X-ray image of a manufactured product such as printed circuit board in a real-time mode and make decisions on whether there are defect symptoms in the product. In this paper we present the current performance of KIMS in product inspection decision.

Original language	English
Pages (from-to)	244-248
Number of pages	5
Journal	Computers and Industrial Engineering
Volume	19
Issue number	1-4
DOIs	https://doi.org/10.1016/0360-8352(90)90114-2
Publication status	Published - 1990

All Science Journal Classification (ASJC) codes

Computer Science(all)
Engineering(all)

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10.1016/0360-8352(90)90114-2

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title = "The performance of KIMS in image recognition tasks",

abstract = "KIMS is an acronym for a Knowledge-Based Image Management System developed in the Robotics and Artificial Intelligence Laboratory (RAIL) at North Carolina A&T State University. KIMS model architecture consists of rules which are developed through statistical experimentation with thresholding and quality control chart algorithms. The control architecture of KIMS is driven by the pattern of these rules. KIMS can analyze features of an X-ray image of a manufactured product such as printed circuit board in a real-time mode and make decisions on whether there are defect symptoms in the product. In this paper we present the current performance of KIMS in product inspection decision.",

author = "Ntuen, {Celestine A.} and Park, {Eui H.} and Park, {Young H.} and Kim, {Jung H.} and Sohn, {Kwang H.}",

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AU - Park, Eui H.

AU - Park, Young H.

AU - Kim, Jung H.

AU - Sohn, Kwang H.

PY - 1990

Y1 - 1990

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AB - KIMS is an acronym for a Knowledge-Based Image Management System developed in the Robotics and Artificial Intelligence Laboratory (RAIL) at North Carolina A&T State University. KIMS model architecture consists of rules which are developed through statistical experimentation with thresholding and quality control chart algorithms. The control architecture of KIMS is driven by the pattern of these rules. KIMS can analyze features of an X-ray image of a manufactured product such as printed circuit board in a real-time mode and make decisions on whether there are defect symptoms in the product. In this paper we present the current performance of KIMS in product inspection decision.

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ER -

The performance of KIMS in image recognition tasks

Abstract

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