Competitive STDP-based spike pattern learning
T Masquelier, R Guyonneau, SJ Thorpe - Neural computation, 2009 - direct.mit.edu
Recently it has been shown that a repeating arbitrary spatiotemporal spike pattern hidden in
equally dense distracter spike trains can be robustly detected and learned by a single …
equally dense distracter spike trains can be robustly detected and learned by a single …
Object class recognition and localization using sparse features with limited receptive fields
J Mutch, DG Lowe - International Journal of Computer Vision, 2008 - Springer
We investigate the role of sparsity and localized features in a biologically-inspired model of
visual object classification. As in the model of Serre, Wolf, and Poggio, we first apply Gabor …
visual object classification. As in the model of Serre, Wolf, and Poggio, we first apply Gabor …
Sparsity-regularized HMAX for visual recognition
About ten years ago, HMAX was proposed as a simple and biologically feasible model for
object recognition, based on how the visual cortex processes information. However, the …
object recognition, based on how the visual cortex processes information. However, the …
Learning to recognize objects using waves of spikes and spike timing-dependent plasticity
T Masquelier, SJ Thorpe - The 2010 International Joint …, 2010 - ieeexplore.ieee.org
This paper focuses on feedforward spiking neuron models of the visual cortex. Essentially,
we show that a combination of a temporal coding scheme where the most strongly activated …
we show that a combination of a temporal coding scheme where the most strongly activated …
Robust handwritten character recognition with features inspired by visual ventral stream
This paper focuses on the applicability of the features inspired by the visual ventral stream
for handwritten character recognition. A set of scale and translation invariant C2 features are …
for handwritten character recognition. A set of scale and translation invariant C2 features are …
The dopamine circuit as a reward-taxis navigation system
O Karin, U Alon - PLoS computational biology, 2022 - journals.plos.org
Studying the brain circuits that control behavior is challenging, since in addition to their
structural complexity there are continuous feedback interactions between actions and …
structural complexity there are continuous feedback interactions between actions and …
[HTML][HTML] Sparsey™: event recognition via deep hierarchical sparse distributed codes
GJ Rinkus - Frontiers in computational neuroscience, 2014 - frontiersin.org
The visual cortex's hierarchical, multi-level organization is captured in many biologically
inspired computational vision models, the general idea being that progressively larger scale …
inspired computational vision models, the general idea being that progressively larger scale …
A hierarchical sparse coding model predicts acoustic feature encoding in both auditory midbrain and cortex
The auditory pathway consists of multiple stages, from the cochlear nucleus to the auditory
cortex. Neurons acting at different stages have different functions and exhibit different …
cortex. Neurons acting at different stages have different functions and exhibit different …
The role of feedback in a hierarchical model of object perception
S Dura-Bernal, T Wennekers, SL Denham - From Brains to Systems: Brain …, 2011 - Springer
We present a model which stems from a well-established model of object recognition,
HMAX, and show how this feedforward system can include feedback, using a recently …
HMAX, and show how this feedforward system can include feedback, using a recently …
Toward a more biologically plausible model of object recognition
M Kouh - 2007 - dspace.mit.edu
Rapidly and reliably recognizing an object (is that a cat or a tiger?) is obviously an important
skill for survival. However, it is a difficult computational problem, because the same object …
skill for survival. However, it is a difficult computational problem, because the same object …