Spatio-temporal sequence learning of visual place cells for robotic navigation

In this paper, we present a novel biologically-inspired spatio-temporal sequence learning architecture of visual place cells to leverage autonomous navigation. The construction of the place cells originates from the well-known architecture of Hubel and Wiesel to develop simple to complex features in...

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Bibliographische Detailangaben

Hauptverfasser:	Vu Anh Nguyen, Starzyk, Janusz A, Tay, Alex Leng Phuan, Wooi-Boon Goh
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Adaptation model Computer architecture Equations Feature extraction Hierarchical memory architecture Hubel and Wiesel's model KFLANN Navigation Neurons Spatio-Temporal Sequence Learning Visualization
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