Managing the complexity of inner-city scenes: An efficient situation hypotheses selection scheme

Research article (2015 IEEE Intelligent Vehicles Symposium (IV), 2015) · cited 23× · AI/ML
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Managing the complexity of inner-city scenes: An efficient situation hypotheses selection scheme

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Managing the complexity of inner-city scenes: An efficient situation hypotheses selection scheme is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Managing the complexity of inner-city scenes: An efficient situation hypotheses selection scheme. Retrieved May 24, 2026, from https://4ort.xyz/entity/managing-the-complexity-of-inner-city-scenes-an-efficient-situation-hypotheses-selection-scheme
MLA “Managing the complexity of inner-city scenes: An efficient situation hypotheses selection scheme.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/managing-the-complexity-of-inner-city-scenes-an-efficient-situation-hypotheses-selection-scheme.
BibTeX @misc{4ortxyz_managing-the-complexity-of-inner-city-scenes-an-efficient-situation-hypotheses-selection-scheme_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Managing the complexity of inner-city scenes: An efficient situation hypotheses selection scheme}}, year = {2026}, url = {https://4ort.xyz/entity/managing-the-complexity-of-inner-city-scenes-an-efficient-situation-hypotheses-selection-scheme}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Managing the complexity of inner-city scenes: An efficient situation hypotheses selection scheme — https://4ort.xyz/entity/managing-the-complexity-of-inner-city-scenes-an-efficient-situation-hypotheses-selection-scheme (retrieved 2026-05-24)

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