TY  - BOOK
AU  - García Campos,Carlos Alan
AU  - Morales Carbajal,Ricardo
AU  - Okuno,Hirotsugu
ED  - Universidad Autónoma de Baja California.
TI  - A comparative analysis of Gabor filters and biologically inspired learning rules for image classification implementing Spiking Neural Networks 
AV  - QA76.87 G37 2025
PY  - 2025///
CY  - Mexicali, Baja California
KW  - Redes neuronales (Informática)
KW  - Tesis y disertaciones académicas
KW  - Redes neurales (computadores)
KW  - lemb
KW  - Software
N1  - Maestría y Doctorado en Ciencias e Ingeniería; Tesis (Maestría) - - Universidad Autónoma de Baja California, Instituto de Ingeniería, Mexicali, 2025; Incluye referencias bibliográficas
N2  - Plastic changes on the synapse drive by spike-timing have been of great interest
as the main learning rule for spiking neural networks. Spike-timing-based rules are
built to model the behavior of a region on the brain related to experimental data in
neuroscience, therefore can lead to differences in the moment of implementing the
rule within a spiking network. This work compares the performance of a pair-wise
and a triplet STDP with different spike interactions to clear an MNIST classification
task. A bio-inspired preprocessing stage was implemented that consisted of a Gabor
filter (as a model of the simple cells mechanism orientation selectivity) and an input
normalization for a homogeneous brightness level of each image. The highlights
of this work are 1) The consistent improvement of the model accuracy whenever
they added the Gabor filter to the inputs; 2) The input normalization to prevent
the overfitting of the model; 3) The Gabor filter helps to correct decoding of some
images of the dataset on the evaluation test
UR  - https://drive.google.com/file/d/1jUWURFzAfflbH7JzGXP1qUD80Qc8-kcS/view?usp=sharing
ER  -