Time-Varying Image Processing and Moving Object Recognition, by V. Cappellini

By V. Cappellini

  • ...Researchers in photograph verbal exchange, man made intelligence and robotics will locate a lot of interest.
    ASLIB publication Guide, 1997

Show description

By V. Cappellini

  • ...Researchers in photograph verbal exchange, man made intelligence and robotics will locate a lot of interest.
    ASLIB publication Guide, 1997

Show description

Read or Download Time-Varying Image Processing and Moving Object Recognition, 4. Proceedings of the 5th International Workshop Florence, Italy, September 5–6, 1996 PDF

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Additional info for Time-Varying Image Processing and Moving Object Recognition, 4. Proceedings of the 5th International Workshop Florence, Italy, September 5–6, 1996

Example text

The robot in such a configuration was installed in an historical building during the Christmas '93 exhibitions, as reported in [9]. The results has been very encouraging in terms of performance and good acceptance by the people who visited the museum during the exhibition days. 3. ROBOLIFT: AUTONOMOUS FORK-LIFT IN LOGISTIC SERVICES The problem of autonomous transport of material in workshops and warehouses has been traditionally approached through the use of automated guided vehicles (AGV). They have been introduced into the market in the early '70s and have provided significant improvements in terms of efficiency, precision and co-ordination of material flow in manufacturing, as compared to conveyor belts, single track railways, etc.

M. Lan S. Abe. Fuzzy rules extraction directly from numerical data for function approximation. IEEE Transactions on Systems, Man and Cybernetics, 25(1):119129, January 1995. 6. X. M. Mendel. Generating fuzzy rules by learning from examples. IEEE Transactions on Systems, Man and Cybernetics, 22(6):1414-1427, November 1992. 7. Y. C. J. Chiang. Automatic generation of fuzzy control rules by machine learning methods. IEEE Proc. of lnt. Conference on Robotics and Automation, pages 287-292, 1992. 8. Y.

In Proc. of the 1994 IEEE International Conference on Multidensor Fusion and Integration for Intelligent Systems (MFI '94), pages 259-265, Las Vegas, NV, October 1994. 5. M. Lan S. Abe. Fuzzy rules extraction directly from numerical data for function approximation. IEEE Transactions on Systems, Man and Cybernetics, 25(1):119129, January 1995. 6. X. M. Mendel. Generating fuzzy rules by learning from examples. IEEE Transactions on Systems, Man and Cybernetics, 22(6):1414-1427, November 1992. 7. Y.

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