@misc{10498/33156,
year = {2023},
url = {http://hdl.handle.net/10498/33156},
abstract = {Most of widely used datasets are not suitable for Spiking Neural Networks (SNNs) due to the need to encode the static data into spike trains and then put them into the network. In addition, the majority of these datasets have been generated to classify objects and can not be used to solve object tracking problems. Therefore, we propose a new neuromorphic dataset, SpikeBALL, for object tracking that contributes to improve the development of the SNN algorithm for these type of problems.},
publisher = {Ignacio Rojas, Gonzalo Joya, Andreu Catalá},
keywords = {spiking neural networks},
keywords = {event cameras},
keywords = {object tracking,},
keywords = {event-based dataset},
title = {SpikeBALL: Neuromorphic Dataset for Object Tracking},
doi = {10.1007/978-3-031-43078-7_52},
author = {Guerrero Vázquez, Elisa and Quintana Velázquez, Fernando Manuel and Guerrero Lebrero, María de la Paz},
}