Search results for "Context"

CLR James y Stuart Hall: dos intelectuales en dialogía

2005

Paz.Villar@uv.es Además de las visibles coincidencias geográficas y personales que unen a CLR James y Stuart Hall, están las intelectuales, que son evidentes para cualquier lector: su lectura nos descubre a dos marxistas disconformes con la ortodoxia estalinista y heterodoxos, a dos intelectuales orgánicos, preocupados por la independencia y desarrollo del Caribe, y a dos anticolonialistas de educación colonial y británica, que se formaron en el pensamiento europeo. Su encuentro dialógico nos invita a reflexionar acerca de los flujos de pensamiento que ambos han recogido y que han vuelto su obra tan productiva para el siglo XXI. Besides the visible geographical and personal coincidences tha…

Cultura y Derechos Humanos

1999

Context and User-Centered Approaches: Icons in Cross-Cultural Context

2014

Culture is embodied in how people interact with other individuals and with their environment. It is a way of life formed under specific historical, natural and social conditions. Cross-cultural communication environment, user/actor and task/situation is the key triplet in our context research. In this chapter, context is discussed as a multidimensional concept and icons in cross-cultural environments are introduced. The authors present Kiyoki's semantic associative search method, and introduce an example of applying an icon-based platform for cross-cultural communication with Kiyoki’s method for searching and creating context-dependent cross-cultural information. This cross-cultural communi…

Predicting change in middle school students’ leisure‐time physical activity participation: A prospective test of the trans‐contextual model

2020

We applied the trans-contextual model (TCM) to examine the effects of middle school students’ perceived autonomy support from their physical education (PE) teachers on autonomous motivation toward PE in school and, critically, autonomous motivation toward, and actual participation in, leisure-time physical activity (PA). The research adopted a three-wave prospective design enabling the modeling of change in the TCM constructs over time. Middle school students (N = 248) aged from 12 to 16 years reported their perceived autonomy support, autonomous motivation in PE, autonomous motivation toward leisure-time PA, attitudes, subjective norms, perceived behavioral control (PBC), intentions for PA…

Deep CNN-ELM Hybrid Models for Fire Detection in Images

2018

In this paper, we propose a hybrid model consisting of a Deep Convolutional feature extractor followed by a fast and accurate classifier, the Extreme Learning Machine, for the purpose of fire detection in images. The reason behind using such a model is that Deep CNNs used for image classification take a very long time to train. Even with pre-trained models, the fully connected layers need to be trained with backpropagation, which can be very slow. In contrast, we propose to employ the Extreme Learning Machine (ELM) as the final classifier trained on pre-trained Deep CNN feature extractor. We apply this hybrid model on the problem of fire detection in images. We use state of the art Deep CNN…

Support Vector Machines for Crop Classification Using Hyperspectral Data

2003

In this communication, we propose the use of Support Vector Machines (SVM) for crop classification using hyperspectral images. SVM are benchmarked to well–known neural networks such as multilayer perceptrons (MLP), Radial Basis Functions (RBF) and Co-Active Neural Fuzzy Inference Systems (CANFIS). Models are analyzed in terms of efficiency and robustness, which is tested according to their suitability to real–time working conditions whenever a preprocessing stage is not possible. This can be simulated by considering models with and without a preprocessing stage. Four scenarios (128, 6, 3 and 2 bands) are thus evaluated. Several conclusions are drawn: (1) SVM yield better outcomes than neura…

The indexing of persons in news sequences using audio-visual data

2004

We describe a video indexing system that automatically searches for a specific person in a news sequence. The proposed approach combines audio and video confidence values extracted from speaker and face recognition analysis. The system also incorporates a shot selection module that seeks for anchors, where the person on the scene is likely speaking. The system has been extensively tested on several news sequences with very good recognition rates.

Kernels for Remote Sensing Image Classification

2015

Classification of images acquired by airborne and satellite sensors is a very challenging problem. These remotely sensed images usually acquire information from the scene at different wavelengths or spectral channels. The main problems involved are related to the high dimensionality of the data to be classified and the very few existing labeled samples, the diverse noise sources involved in the acquisition process, the intrinsic nonlinearity and non-Gaussianity of the data distribution in feature spaces, and the high computational cost involved to process big data cubes in near real time. The framework of statistical learning in general, and of kernel methods in particular, has gained popul…

Detection of power line insulators on digital images with the use of laser spots

2019

The massive growth of technologies used to register and process digital images allow for their application in evaluating the technical condition of power lines. However, it is not possible without a set of dedicated methods for obtaining diagnostic information based on registered video data. The method described here details the detection of power line insulators in digital images featuring diversified backgrounds using laser spots. The algorithm of detecting an insulator in analysed images is based on testing the digital signal of pixel intensity profiles read between subsequent pairs of laser points in the image. The method is comprised of the following stages: import the image with laser…

Optimized spatio-temporal descriptors for real-time fall detection: comparison of support vector machine and Adaboost-based classification

2013

We propose a supervised approach to detect falls in a home environment using an optimized descriptor adapted to real-time tasks. We introduce a realistic dataset of 222 videos, a new metric allowing evaluation of fall detection performance in a video stream, and an automatically optimized set of spatio-temporal descriptors which fed a supervised classifier. We build the initial spatio-temporal descriptor named STHF using several combinations of transformations of geometrical features (height and width of human body bounding box, the user’s trajectory with her/his orientation, projection histograms, and moments of orders 0, 1, and 2). We study the combinations of usual transformations of the…