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- W2098978078 abstract "For realizing a naturalistic collaboration between humans and robots, we have to establish intention-sharing from the series of motion data that are observed and exchanged between the human and the machine. This is a problem of detecting meanings in the digitized data stream. We propose an approach based on semiosis, and present a number of ways for implementing the ideas using associative neural networks; one is a recurrent neural Elman network and the other one is Grossberg's adaptive resonance theory model. Experimental results are shown and their contributions to the design of a human-machine shared autonomy system are discussed." @default.
- W2098978078 created "2016-06-24" @default.
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- W2098978078 date "2002-11-14" @default.
- W2098978078 modified "2023-09-26" @default.
- W2098978078 title "Self-reflective segmentation of human bodily motions using associative neural networks towards human-machine shared autonomy" @default.
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- W2098978078 doi "https://doi.org/10.1109/cira.2001.1013255" @default.
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