THE PERFORMANCE OF KIMS IN IMAGE RECOGNITION TASKS

被引:1
|
作者
NTUEN, CA [1 ]
PARK, EH [1 ]
PARK, YH [1 ]
KIM, JH [1 ]
SOHN, KH [1 ]
机构
[1] N CAROLINA STATE UNIV,RALEIGH,NC 27695
关键词
D O I
10.1016/0360-8352(90)90114-2
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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.
引用
收藏
页码:244 / 248
页数:5
相关论文
共 50 条
  • [21] Data for Image Recognition Tasks: An Efficient Tool for Fine-Grained Annotations
    Filax, Marco
    Gonschorek, Tim
    Ortmeier, Frank
    ICPRAM: PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION APPLICATIONS AND METHODS, 2019, : 900 - 907
  • [22] Image Recognition of a Bolt in Power Distribution Line Maintenance tasks for an Autonomous Robot
    Yang, Xianjing
    Hida, Minoru
    Suzuki, Yoshitatsu
    Emoto, Kengo
    Tatsuno, Kyoichi
    2013 INTERNATIONAL SYMPOSIUM ON MICRO-NANOMECHATRONICS AND HUMAN SCIENCE (MHS), 2013,
  • [25] EFFECTS OF ORIENTING TASKS ON THE RECALL AND RECOGNITION PERFORMANCE OF SUBJECTS DIFFERING IN AGE
    MASON, SE
    DEVELOPMENTAL PSYCHOLOGY, 1979, 15 (04) : 467 - 469
  • [26] HOW PRECISE ARE PERFORMANCE ESTIMATES FOR TYPICAL MEDICAL IMAGE SEGMENTATION TASKS?
    El Jurdi, Rosana
    Colliot, Olivier
    2023 IEEE 20TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING, ISBI, 2023,
  • [27] The New Dataset MITWPU-1K for Object Recognition and Image Captioning Tasks
    Bhalekar, Madhuri
    Bedekar, Mangesh
    ENGINEERING TECHNOLOGY & APPLIED SCIENCE RESEARCH, 2022, 12 (04) : 8803 - 8808
  • [28] Mapping Schemes of Image Recognition Tasks onto Highly Parallel SIMD/MIMD Processors
    Kyo, Shorin
    Nomoto, Shohei
    Okazaki, Shinichiro
    2009 THIRD ACM/IEEE INTERNATIONAL CONFERENCE ON DISTRIBUTED SMART CAMERAS, 2009, : 465 - 470
  • [29] Effective Conversion of a Convolutional Neural Network into a Spiking Neural Network for Image Recognition Tasks
    Ngu, Huynh Cong Viet
    Lee, Keon Myung
    APPLIED SCIENCES-BASEL, 2022, 12 (11):
  • [30] Convolutional Neural Networks Based on RRAM Devices for Image Recognition and Online Learning Tasks
    Dong, Zhen
    Zhou, Zheng
    Li, Zefan
    Liu, Chen
    Huang, Peng
    Liu, Lifeng
    Liu, Xiaoyan
    Kang, Jinfeng
    IEEE TRANSACTIONS ON ELECTRON DEVICES, 2019, 66 (01) : 793 - 801