Further, there lacks a comprehensive review and comparison of existing approaches for location reference recognition, which is the first and a core step of geoparsing.
Event-based sensors (e. g., DVS cameras) are capable of higher dynamic range, higher temporal resolution, lower time latency, and better power efficiency compared to conventional devices (e. g., RGB cameras).
To our surprise, the SBCC framework could provide an alternative view to explain a set of generalized cross-correlation (GCC) methods and comprehend the meaning of parameters.
Experiments on two event datasets (N-Caltech101 and N-Cars) demonstrate that EventDrop can significantly improve the generalization performance across a variety of deep networks.
In this paper, we propose a novel spiking graph neural network for event-based tactile object recognition.