Search results for "Map"
showing 10 items of 3484 documents
Introducing the BICA Society
2010
The Biologically Inspired Cognitive Architectures Society, or the BICA Society, is a recently formed nonprofit organization. The purpose of the Society is to promote and facilitate the transdisciplinary study of biologically inspired cognitive architectures (BICA), in particular, aiming at the emergence of a unifying, generally accepted framework for the design, characterization and implementation of human-level cognitive architectures. The First International Conference on Biologically Inspired Cognitive Architectures (BICA 2010) is at the same time officially the First Annual Meeting of the BICA Society.
Soil Water Content Diachronic Mapping: An FFT Frequency Analysis of a Temperature–Vegetation Index
2020
Among the indirect estimation approaches of soil water content in the upper layer of the soil, the &ldquo
Increasing Motivation in a Multicultural Learning Setting
2010
This paper presents a study carried out at Hirubide Secondary School in the Basque Country with the aim of evaluating whether the use of the CM-ED Concept Map EDitor increases student motivation and engagement in the learning process. During the last decades, motivating students has increasingly become a problem for educators even more in multicultural educational settings.
The Usage of Quadtree in Deep Neural Networks to Represent Data For Navigation From a Monocular Camera
2022
Depth acquisition represents a key element for navigation tasks. It is, therefore, one of the major research topics in computer vision. Many approaches have been developed to address this problem by constructing the depth from series of images. However, there is a minimal case proposing a prediction from a single image, made possible with the emergence of deep learning approaches. The latter makes it possible to consider a reduction in both hardware and computing time costs, which is beneficial for embedded systems. However, network architecture remains a heavy process requiring a lot of GPU memory. Few approaches have proposed addressing this problem by developing lightweight architectures…
Action Recognition based on Hierarchical Self-Organizing Maps
2014
We propose a hierarchical neural architecture able to recognise observed human actions. Each layer in the architecture represents increasingly complex human activity features. The first layer consists of a SOM which performs dimensionality reduction and clustering of the feature space. It represents the dynamics of the stream of posture frames in action sequences as activity trajectories over time. The second layer in the hierarchy consists of another SOM which clusters the activity trajectories of the first-layer SOM and thus it learns to represent action prototypes independent of how long the activity trajectories last. The third layer of the hierarchy consists of a neural network that le…
Postural Control Profiles of Typically Developing Children From 6 to 12 Years old: An Approach Using Self-Organizing Maps
2020
The purposes of the present study were a) to establish postural control profiles for individuals 6–12 years of age, b) to analyze the participants’ characteristics (age, sex, weight, height, and physical activity) in those profiles, and c) to analyze the influence of visual information in the profiles found. Two hundred and eight typically developing children aged 6–12 years performed two trials in bipedal standing position with eyes open and closed. Feature extraction involved time, frequency, and sway-density plot variables using signals from the center of pressure. A Self-Organizing Map was used to classify and visualize the values of the participants in all the postural control variable…
6 Self-organising Maps To Analyse Effects Of Low Intensity Concentric Combined With Blood Flow Restriction
2014
Introduction Self-Organising Maps (SOM) are a type of Artificial Neural Network (ANN) model used to visualise multidimensional data [Kohonen-00]. SOM provides a correspondence between the original N-dimensional space and a twodimensional space [Haykin-08]. In the case presented in this work, this means that two subjects with similar values of the different variables should appear near in the two-dimensional space [Kohonen-00], [Haykin-08]. Method In order to test this method, 15 athletes were selected. Subjects’ measurements were performed in three different periods: before the exercise test, immediately after performing the exercise and twenty-four hours later. The control measures were th…
Competing Effects Between Screen Media Time and Physical Activity in Adolescent Girls: Clustering a Self-Organizing Maps Analysis.
2016
Background:Previous research shows contradictory findings on potential competing effects between sedentary screen media usage (SMU) and physical activity (PA). This study examined these effects on adolescent girls via self-organizing maps analysis focusing on 3 target profiles.Methods:A sample of 1,516 girls aged 12 to 18 years self-reported daily time engagement in PA (moderate and vigorous intensity) and in screen media activities (TV/video/DVD, computer, and videogames), separately and combined.Results:Topological interrelationships from the 13 emerging maps indicated a moderate competing effect between physically active and sedentary SMU patterns. Higher SES and overweight status were l…
Timbre Similarity: Convergence of Neural, Behavioral, and Computational Approaches
1998
The present study compared the degree of similarity of timbre representations as observed with brain recordings, behavioral studies, and computer simulations. To this end, the electrical brain activity of subjects was recorded while they were repetitively presented with five sounds differing in timbre. Subjects read simultaneously so that their attention was not focused on the sounds. The brain activity was quantified in terms of a change-specific mismatch negativity component. Thereafter, the subjects were asked to judge the similarity of all pairs along a five-step scale. A computer simulation was made by first training a Kohonen self-organizing map with a large set of instrumental sounds…
Neural networks for animal science applications: Two case studies
2006
Abstract Artificial neural networks have shown to be a powerful tool for system modelling in a wide range of applications. In this paper, we focus on neural network applications to intelligent data analysis in the field of animal science. Two classical applications of neural networks are proposed: time series prediction and clustering. The first task is related to the prediction of weekly milk production in goat flocks, which includes a knowledge discovery stage in order to analyse the relative relevance of the different variables. The second task is the clustering of goat flocks; it is used to analyse different livestock surveys by using self-organizing maps and the adaptive resonance theo…