Search results for "Age class"

El aula de comunicación y lenguaje y la inclusión escolar. Dificultades y estrategias de intervención / Communicatio classroomn and language and scho…

2016

This research shows a case study of two students schooled in the Communication and Language classroom of a Valencian school. The main goal is to understand the situation of inclusive education of these students. With this aim, it has collected information through record sheets, interviews, surveys, informal conversations and field journal that allowed us to do a qualitative analysis. We have described the difficulties that hinder the transition to ordinary classroom and we have analyzed the correspondence between intervention strategies of both classrooms. With these results, we reflect on the accomplishment of the goal of creating C&L classrooms: the progressive inclusion in ordinary class…

Revista electrónica interuniversitaria de formación del profesorado

2016

Actualmente la inclusión es una de las mayores prioridades tanto del ámbito educativo como de la sociedad en general. El trabajo que exponemos se enmarca en el seno del debate abierto en torno a las distintas opiniones y creencias existentes sobre el tema. Concretamente, mostramos los resultados obtenidos en un estudio de caso, al evaluar las percepciones del profesorado y familias del alumnado de un aula de Comunicación y Lenguaje valenciana, sobre el proceso de inclusión realizado a lo largo de sus cinco años de funcionamiento. A través de un diseño de investigación mixto utilizamos instrumentos de recogida de datos cualitativos tales como la entrevista y la observación participante así c…

Dataset shift adaptation with active queries

2011

In remote sensing image classification, it is commonly assumed that the distribution of the classes is stable over the entire image. This way, training pixels labeled by photointerpretation are assumed to be representative of the whole image. However, differences in distribution of the classes throughout the image make this assumption weak and a model built on a single area may be suboptimal when applied to the rest of the image. In this paper, we investigate the use of active learning to correct the shifts that may appear when training and test data do not come from the same distribution. Experiments are carried out on a VHR remote sensing classification scenario showing that active learni…

Microaneurysm detection with radon transform-based classification on retina images.

2012

The creation of an automatic diabetic retinopathy screening system using retina cameras is currently receiving considerable interest in the medical imaging community. The detection of microaneurysms is a key element in this effort. In this work, we propose a new microaneurysms segmentation technique based on a novel application of the radon transform, which is able to identify these lesions without any previous knowledge of the retina morphological features and with minimal image preprocessing. The algorithm has been evaluated on the Retinopathy Online Challenge public dataset, and its performance compares with the best current techniques. The performance is particularly good at low false p…

Using active learning to adapt remote sensing image classifiers

2011

The validity of training samples collected in field campaigns is crucial for the success of land use classification models. However, such samples often suffer from a sample selection bias and do not represent the variability of spectra that can be encountered in the entire image. Therefore, to maximize classification performance, one must perform adaptation of the first model to the new data distribution. In this paper, we propose to perform adaptation by sampling new training examples in unknown areas of the image. Our goal is to select these pixels in an intelligent fashion that minimizes their number and maximizes their information content. Two strategies based on uncertainty and cluster…

Texture classification for content-based image retrieval

2002

An original approach to texture-based classification of regions, for image indexing and retrieval, is presented. The system addresses automatic macro-textured ROI detection, and classification: we focus our attention on those objects that can be characterized by a texture as a whole, like trees, flowers, walls, clouds, and so on. The proposed architecture is based on the computation of the /spl lambda/ vector from each selected region, and classification of this feature by means of a pool of suitably trained support vector machines (SVM). This approach is an extension of the one previously developed by some of the authors to classify image regions on the basis of the geometrical shape of th…

A Conceptual Probabilistic Model for the Induction of Image Semantics

2010

In this paper we propose a model based on a conceptual space automatically induced from data. The model is inspired to a well-founded robotics cognitive architecture which is organized in three computational areas: sub-conceptual, linguistic and conceptual. Images are objects in the sub-conceptual area, that become "knoxels" into the conceptual area. The application of the framework grants the automatic emerging of image semantics into the linguistic area. The core of the model is a conceptual space induced automatically from a set of annotated images that exploits and mixes different information concerning the set of images. Multiple low level features are extracted to represent images and…

Method for Classifying a Digital Image

2010

Introducing Pseudo-Singularity Points for Efficient Fingerprints Classification and Recognition

2010

Fingerprint classification and matching are two key issues in automatic fingerprint recognition. Generally, fingerprint recognition is based on a set of relevant local characteristics, such as ridge ending and bifurcation (minutiae). Fingerprint classification is based on fingerprint global features, such as core and delta singularity points. Unfortunately, singularity points are not always present in a fingerprint image: the acquisition process is not ideal, so that the fingerprint is broken, or the fingerprint belongs to the arch class. In the above cases, pseudo-singularity-points will be detected and extracted to make possible fingerprint classification and matching. As result, fingerpr…

Multi-temporal and Multi-source Remote Sensing Image Classification by Nonlinear Relative Normalization

2016

Remote sensing image classification exploiting multiple sensors is a very challenging problem: data from different modalities are affected by spectral distortions and mis-alignments of all kinds, and this hampers re-using models built for one image to be used successfully in other scenes. In order to adapt and transfer models across image acquisitions, one must be able to cope with datasets that are not co-registered, acquired under different illumination and atmospheric conditions, by different sensors, and with scarce ground references. Traditionally, methods based on histogram matching have been used. However, they fail when densities have very different shapes or when there is no corres…