Urban Road Lane Number Mining from Low-Frequency Floating Car Data Based on Deep Learning

Lane-level road information is especially crucial now that high-precision navigation maps are in more demand. Road information may be obtained rapidly and affordably by mining floating vehicle data (FCD). A method is proposed to extract the number of lanes on urban roads by combining deep learning a...

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Vydané v:	ISPRS international journal of geo-information Ročník 12; číslo 11; s. 467
Hlavní autori:	Li, Xiaolong, Zhang, Yun, Xiang, Longgang, Wu, Tao
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.11.2023
Predmet:	Accuracy Algorithms Classification Cleaning Clustering Computational linguistics DBSCAN clustering algorithm Deep learning extracts FCD Floating Fuzzy logic Language processing LeNet-5 model mining Natural language interfaces Navigation number of lanes prediction roads Roads & highways sampling Urban areas China
ISSN:	2220-9964, 2220-9964
On-line prístup:	Získať plný text
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