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Textural Features for Hyperspectral Pixel Classification
(Springer Berlin Heidelberg, 2009)
Hyperspectral remote sensing provides data in large amounts from a wide range of wavelengths in the spectrum and the possibility of distinguish subtle differences in the image. For this reason, the process of band selection ...
Scale Analysis of Several Filter Banks for Color Texture Classification
(Springer Berlin Heidelberg, 2009)
We present a study of the contribution of the different scales used by several feature extraction methods based on filter banks for color texture classification. Filter banks used for textural characterization purposes are ...
Multi-spectral Texture Characterisation for Remote Sensing Image Segmentation
(Springer Berlin Heidelberg, 2009)
A multi-spectral texture characterisation model is proposed, the Multi-spectral Local Differences Texem – MLDT, as an affordable approach to be used in multi-spectral images that may contain large number of bands. The MLDT ...
Parallel Interconnection of Broadcast Systems with Multiple FIFO Channels
(Springer Berlin Heidelberg, 2009)
This paper proposes new protocols for the interconnection of FIFO- and causal-ordered broadcast systems, thus increasing their scalability. They use several interconnection links between systems, which avoids bottleneck ...
Mobile Access to Sensor Network: A Use Case on Wildfire Monitoring
(Springer International Publishing, 2014)
These networks provide large volumes of data in many different formats, resolution and scales. The data are of different types and character: from meteorological conditions to air quality and the concentrations of pollutants ...
One-Sided Prototype Selection on Class Imbalanced Dissimilarity Matrices
(Springer Berlin Heidelberg, 2012)
In the dissimilarity representation paradigm, several prototype selection methods have been used to cope with the topic of how to select a small representation set for generating a low-dimensional dissimilarity space. In ...
Edited Nearest Neighbor Rule for Improving Neural Networks Classifications
(Springer Berlin Heidelberg, 2010)
The quality and size of the training data sets is a critical stage on the ability of the artificial neural networks to generalize the characteristics of the training examples. Several approaches are focused to form training ...
Continuous Level of Detail for Large Scale Rendering of 3D Animated Polygonal Models
(Springer Berlin Heidelberg, 2012)
Current simulation applications are mainly focused on the efficient management of scenarios with static objects. However, managing dynamic objects, such as animated characters, is very different and requires more specific ...
Relief Patterned-Tile Classification for Automatic Tessella Assembly
(Springer Berlin Heidelberg, 2010)
This paper presents the detection and classification part of an industrial machine for automated assembly of decorative tessellae over patterned tiles that have significant reliefs. The machine consists of two vision systems ...
Gender Classification from Pose-Based GEIs
(Springer Berlin Heidelberg, 2012)
This paper introduces a new approach for gait-based gender classification in which some key biomechanical poses of a gait pattern are represented by partial Gait Energy Images (GEIs). These pose-based GEIs can more accurately ...