Biologically inspired deep convolutional neural networks (CNNs), trained for computer vision tasks, have been found to predict cortical responses with remarkable accuracy. However, the internal operations of these models remain poorly understood, and...
Neural networks : the official journal of the International Neural Network Society
Apr 16, 2018
Shaping the collision selectivity in vision-based artificial collision-detecting systems is still an open challenge. This paper presents a novel neuron model of a locust looming detector, i.e. the lobula giant movement detector (LGMD1), in order to p...
International journal of neural systems
Apr 12, 2018
Although robot technology has been successfully used to empower people who suffer from motor disabilities to increase their interaction with their physical environment, it remains a challenge for individuals with severe motor impairment, who do not h...
Neural networks : the official journal of the International Neural Network Society
Mar 20, 2018
This paper presents an algorithm for nonnegative matrix factorization based on a biconvex optimization formulation. First, a discrete-time projection neural network is introduced. An upper bound of its step size is derived to guarantee the stability ...
Neural networks : the official journal of the International Neural Network Society
Mar 20, 2018
Learning from label proportions (LLP), in which the training data is in the form of bags and only the proportion of each class in each bag is available, has attracted wide interest in machine learning. However, how to solve high-dimensional LLP probl...
The brain represents visual objects with topographic cortical patterns. To address how distributed visual representations enable object categorization, we established predictive encoding models based on a deep residual network, and trained them to pr...
Recent technological advances in machine learning offer the possibility of decoding complex datasets and discern latent patterns. In this study, we adopt Liquid State Machines (LSM) to recognize the emotional state of an individual based on EEG data....
Neural networks : the official journal of the International Neural Network Society
Jan 10, 2018
The mathematical relation between a vector electric field and its corresponding scalar potential field is useful to formulate computational problems of lower/middle-order visual processing, specifically related to the assignment of borders to the sid...
Neural networks : the official journal of the International Neural Network Society
Dec 23, 2017
Previous studies have shown that spike-timing-dependent plasticity (STDP) can be used in spiking neural networks (SNN) to extract visual features of low or intermediate complexity in an unsupervised manner. These studies, however, used relatively sha...
OBJECTIVE: Conventional decoding pipeline for brain-machine interfaces (BMIs) consists of chained different stages of feature extraction, time-frequency analysis and statistical learning models. Each of these stages uses a different algorithm trained...