RT conference output
T1 SpikeBALL: Neuromorphic Dataset for Object Tracking
A1 Guerrero Vázquez, Elisa
A1 Quintana Velázquez, Fernando Manuel
A1 Guerrero Lebrero, María de la Paz
A2 Ingeniería Informática
K1 spiking neural networks
K1 event cameras
K1 object tracking,
K1 event-based dataset
AB 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.
PB Ignacio Rojas, Gonzalo Joya, Andreu Catalá
SN 9783031430770
YR 2023
FD 2023
LK http://hdl.handle.net/10498/33156
UL http://hdl.handle.net/10498/33156
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 10-may-2026