Search results for "Percept"
showing 10 items of 3839 documents
BELM: Bayesian Extreme Learning Machine
2011
The theory of extreme learning machine (ELM) has become very popular on the last few years. ELM is a new approach for learning the parameters of the hidden layers of a multilayer neural network (as the multilayer perceptron or the radial basis function neural network). Its main advantage is the lower computational cost, which is especially relevant when dealing with many patterns defined in a high-dimensional space. This brief proposes a bayesian approach to ELM, which presents some advantages over other approaches: it allows the introduction of a priori knowledge; obtains the confidence intervals (CIs) without the need of applying methods that are computationally intensive, e.g., bootstrap…
A VR-Enhanced Rollover Car Simulator and Edutainment Application for Increasing Seat Belt Use Awareness
2021
Most countries have active road safety policies that seek the objective of reducing deaths in traffic accidents. One of the main factors in this regard is the awareness of the safety measures, one of the most important being the correct usage of the seat belt, a device that is known to save thousands of lives every year. The presented work shows a VR-enhanced edutainment application designed to increase awareness on the use of seat belts. For this goal, a motorized rollover system was developed that, synchronized with a VR application (shown in a head-mounted display for each user inside a real car), rolls over this car with up to four passengers inside. This way, users feel the sensations …
A Fly-Inspired Mushroom Bodies Model for Sensory-Motor Control Through Sequence and Subsequence Learning
2016
Classification and sequence learning are relevant capabilities used by living beings to extract complex information from the environment for behavioral control. The insect world is full of examples where the presentation time of specific stimuli shapes the behavioral response. On the basis of previously developed neural models, inspired by Drosophila melanogaster, a new architecture for classification and sequence learning is here presented under the perspective of the Neural Reuse theory. Classification of relevant input stimuli is performed through resonant neurons, activated by the complex dynamics generated in a lattice of recurrent spiking neurons modeling the insect Mushroom Bodies n…
Perceptual adaptive insensitivity for support vector machine image coding.
2005
Support vector machine (SVM) learning has been recently proposed for image compression in the frequency domain using a constant epsilon-insensitivity zone by Robinson and Kecman. However, according to the statistical properties of natural images and the properties of human perception, a constant insensitivity makes sense in the spatial domain but it is certainly not a good option in a frequency domain. In fact, in their approach, they made a fixed low-pass assumption as the number of discrete cosine transform (DCT) coefficients to be used in the training was limited. This paper extends the work of Robinson and Kecman by proposing the use of adaptive insensitivity SVMs [2] for image coding u…
Distinct Patterns of Functional Connectivity During the Comprehension of Natural, Narrative Speech.
2020
Recent continuous task studies, such as narrative speech comprehension, show that fluctuations in brain functional connectivity (FC) are altered and enhanced compared to the resting state. Here, we characterized the fluctuations in FC during comprehension of speech and time-reversed speech conditions. The correlations of Hilbert envelope of source-level EEG data were used to quantify FC between spatially separate brain regions. A symmetric multivariate leakage correction was applied to address the signal leakage issue before calculating FC. The dynamic FC was estimated based on a sliding time window. Then, principal component analysis (PCA) was performed on individually concatenated and te…
Multilayer perceptron neural networks and radial-basis function networks as tools to forecast accumulation of deoxynivalenol in barley seeds contamin…
2011
The capacity of multi-layer perceptron artificial neural networks (MLP-ANN) and radial-basis function networks (RBFNs) to predict deoxynivalenol (DON) accumulation in barley seeds contaminated with Fusarium culmorum under different conditions has been assessed. Temperature (20-28 °C), water activity (0.94-0.98), inoculum size (7-15 mm diameter), and time were the inputs while DON concentration was the output. The dataset was used to train, validate and test many ANNs. Minimizing the mean-square error (MSE) was used to choose the optimal network. Single-layer perceptrons with low number of hidden nodes proved better than double-layer perceptrons, but the performance depended on the training …
Kernel manifold alignment for domain adaptation
2016
The wealth of sensory data coming from different modalities has opened numerous opportu- nities for data analysis. The data are of increasing volume, complexity and dimensionality, thus calling for new methodological innovations towards multimodal data processing. How- ever, multimodal architectures must rely on models able to adapt to changes in the data dis- tribution. Differences in the density functions can be due to changes in acquisition conditions (pose, illumination), sensors characteristics (number of channels, resolution) or different views (e.g. street level vs. aerial views of a same building). We call these different acquisition modes domains, and refer to the adaptation proble…
Interaction with Information Graphics: A Content-Based Approach
2009
Understanding information graphics rely on thought process of graphics' reader, and thinking has the most important role in interpretation and exploitation. We are interested in the cognitive mechanisms underlying interaction with information graphics. In this study, we studied those cognitive processes which are employed when interacting with information graphics. Based on these experiments, we have separated four different types of thought processes which occur during the interactions with information graphics. We propose that these thought processes are apperception, restructuring, reflection and construction.
Introducing implicit learning: from the laboratory to the real life
2010
The dissociation between implicit and explicit cognition has a long history in psychology. As early as 1920, Clark Hull (25) investigated the learning of Chinese ideographs and identified the process of concept formation by abstraction of common elements, a process that occurs without explicit knowledge from the subjects of these regularities. Perceptual learning is another example of those processes that take place largely in the absence of awareness of the rules that govern the stimulations of the environment. Helmholtz (24) was one of the first to refer to implicit inference made by the perceptual system and to perceptual learning. Some years later, the distinction between implicit and e…
Stereopsis assessment at multiple distances with an iPad application
2017
[EN] We present a new application for iPad for screening stereopsis at multiple distances that allows testing up to ten levels of stereoacuity at each distance. Our approach is based on a random dot stereogram viewable with anaglyph spectacles. Sixty-five subjects with no ocular diseases, wearing their habitual correction were measured at 3 m and 0.5 m. Results were compared with a standard stereoscopic test (TNO). We found not statistically significant differences between both tests, but our method achieved higher reproducibility. Applications in visual screening programs and to design and use of 3D displays, are suggested. (C) 2017 Elsevier B.V. All rights reserved.