Intelligent CAI system for artistic calligraphy evaluation by using neural-fuzzy reasoning

被引:0
|
作者
Nagayama, I
Takara, T
机构
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This study describes on-going project of the drawing understanding and evaluation framework to construct artistic calligraphy oriented CAI system for artistic education. This new CAI system employs an understanding process that complies with the understanding rules, which are easily obtained by the system and user. The rule set for evaluation and understanding the calligraphy that created by the user are compiled with the rule obtained by the system. However, fine tuning is required to establish effective evaluation and understanding rules. To establish the collaborative ICAI system, we extended the system using a newly constructed understanding rule generating support system. The resultant integrated system is based on man-machine cooperation type interface, and can automatically generate rules from user-provided simple interactions using a graphical user interface. To obtain efficient rule generation and learning strategy, the system employs the neural-fuzzy tuning as a learning scheme.
引用
收藏
页码:634 / 636
页数:3
相关论文
共 50 条
  • [21] Theory of neural-fuzzy control system and computer realization
    Wang Hong
    Proceedings of the 2007 Chinese Control and Decision Conference, 2007, : 450 - 452
  • [22] An intelligent neural-fuzzy model for an in-process surface roughness monitoring system in end milling operations
    Huang, PoTsang B.
    JOURNAL OF INTELLIGENT MANUFACTURING, 2016, 27 (03) : 689 - 700
  • [23] An intelligent neural-fuzzy model for an in-process surface roughness monitoring system in end milling operations
    PoTsang B. Huang
    Journal of Intelligent Manufacturing, 2016, 27 : 689 - 700
  • [24] Power Grid Development Level Evaluation Based on Adaptive Neural-fuzzy Inference System
    Wu, Han
    Niu, Dongxiao
    Liu, Weidong
    Sun, Ke
    13TH GLOBAL CONGRESS ON MANUFACTURING AND MANAGEMENT, 2017, 174 : 850 - 857
  • [25] A neural-fuzzy system for congestion control in ATM networks
    Lee, SJ
    Hou, CL
    IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2000, 30 (01): : 2 - 9
  • [26] Material property prediction using neural-fuzzy network
    Chen, MY
    PROCEEDINGS OF THE 3RD WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-5, 2000, : 1092 - 1097
  • [27] Argumentation system for intelligent assistants using fuzzy-based reasoning
    Koivuaho, T.
    Ibrahim, M.
    Ummul, F.
    Oussalah, M.
    DATA SCIENCE AND KNOWLEDGE ENGINEERING FOR SENSING DECISION SUPPORT, 2018, 11 : 608 - 616
  • [28] Sensorless Speed Control of Induction Motors using Adaptive Neural-Fuzzy Inference System
    Moghadasian, Mahmood
    Amiri, Mohamad
    2011 IEEE/ASME INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT MECHATRONICS (AIM), 2011, : 1028 - 1033
  • [29] Neural-fuzzy control of truck backer-upper system using a clustering method
    Li, Ying
    Li, Yuanchun
    NEUROCOMPUTING, 2007, 70 (4-6) : 680 - 688
  • [30] Automatic color identification in printed fabrics by a neural-fuzzy system
    Xu, BG
    Lin, S
    AATCC REVIEW, 2002, 2 (09) : 42 - 45