Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Scott D. G. Smith"'
Publikováno v:
Robotics and Autonomous Systems. 49:7-12
The attendees of the Knowledge Representation and Ontologies for Autonomous Systems Symposium 1 applied their collective intelligence in an attempt to solve one of the universe's great challenges: how do you autonomously collect garbage from an airpo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::47075cab98b531c6ea4a1ad906ac7609
https://doi.org/10.1016/j.robot.2004.07.013
https://doi.org/10.1016/j.robot.2004.07.013
Publikováno v:
Robotics and Autonomous Systems. 49:123-133
We report the results of a first implementation demonstrating the use of an ontology to support reasoning about obstacles to improve the capabilities and performance of on-board route planning for autonomous vehicles. This is part of an overall effor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::39271a9361ffc610ba38bf0b195ee14a
https://doi.org/10.1016/j.robot.2004.07.020
https://doi.org/10.1016/j.robot.2004.07.020
Publikováno v:
The Knowledge Engineering Review. 18:243-255
This paper explores the hypothesis that ontologies can be used to improve the capabilities and performance of on-board route planning for autonomous vehicles. We name a variety of general benefits that ontologies may provide, and list numerous specif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0fdb93a68834013560683cc94dbcd665
https://doi.org/10.1017/s0269888904000050
https://doi.org/10.1017/s0269888904000050
Publikováno v:
The International Journal of Advanced Manufacturing Technology. 8:269-273
Group technology is an approach to manufacturing that attempts to enhance production efficiency by grouping similar activities and tasks together. The results of this process are then used in the execution of similar tasks and activities. This concep
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bab0a8cc7f4c2ce115e0ffef00379228
https://doi.org/10.1007/bf01748637
https://doi.org/10.1007/bf01748637
Publikováno v:
IEEE Transactions on Neural Networks. 4:9-20
LAPART, a neural network architecture for logical inferencing and supervised learning is discussed. Emphasizing its use in recognizing familiar sequences of patterns by verifying pattern pairs inferred from prior experience. It consists of interconne
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::884a96929c010d277705587612deae64
https://doi.org/10.1109/72.182691
https://doi.org/10.1109/72.182691
Publikováno v:
IEEE transactions on neural networks. 8(4)
We describe a neural information retrieval system (NIRS), now in production within the Boeing Company, which has been developed for the identification and retrieval of engineering designs. Two-dimensional and three-dimensional representations of engi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c3d564f90d4e392254e7897df00bc16a
https://pubmed.ncbi.nlm.nih.gov/18255688
https://pubmed.ncbi.nlm.nih.gov/18255688
Publikováno v:
SPIE Proceedings.
ormance of this compressed algorithm is compared to that of the regular algorithm on real engineering designs anda significant savings in memory storage as well as a speed up in execution is observed. In addition, we will describe a"neural database"
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d42a46a2590ff4f6f1a46cdc86084424
https://doi.org/10.1117/12.44994
https://doi.org/10.1117/12.44994
Publikováno v:
IJCNN-91-Seattle International Joint Conference on Neural Networks.
Summary form only given, as follows. The feasibility of training an adaptive resonance theory (ART-1) network to first cluster aircraft parts into families, and then to recall the most similar family when presented a new part has been demonstrated, A
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::58ea60ad72e5cfcfb8c86685212343ba
https://doi.org/10.1109/ijcnn.1991.155571
https://doi.org/10.1109/ijcnn.1991.155571