DeepLabV3+-Based Semantic Annotation Refinement for SLAM in Indoor Environments

Visual SLAM systems frequently encounter challenges in accurately reconstructing three-dimensional scenes from monocular imagery in semantically deficient environments, which significantly compromises robotic operational efficiency. While conventional manual annotation approaches can provide supplem...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Sensors (Basel, Switzerland) Jg. 25; H. 11; S. 3344
Hauptverfasser:	Wei, Shuangfeng, Tang, Hongrui, Liu, Changchang, Yang, Tong, Zhou, Xiaohang, Zlatanova, Sisi, Fan, Junlin, Tu, Liping, Mao, Yaqin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 26.05.2025 MDPI
Schlagworte:	Accuracy Algorithms Annotations Clustering Data processing Efficiency image semantic segmentation Localization Mapping Neural networks Optimization point cloud semantic annotation Research methodology scene understanding Semantics Sensors Telecommunication systems visual SLAM China image semantic segmentation clustering scene understanding visual SLAM point cloud semantic annotation
ISSN:	1424-8220, 1424-8220
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!