To extract salient features from images is significant for image classification. Deformable
objects suffer from the problem that a number of pixels may have varying intensities. In other …

The frequent growth of visual data, either by countless monitoring video cameras wherever
we go or the popularization of mobile devices that allow each person to create and edit their …

Abstract Description and classification of face images is a significant task of computer vision,
machine learning and pattern recognition communities. In the past, researchers have made …

Collaborative representation classification (CRC) is an important sparse method, which is
easy to carry out and uses a linear combination of training samples to represent a test …

We show that no fixed number of parallel repetitions suffices in order to reduce the error in
two-prover one-round proof systems from one constant to another. Our results imply that the …

Plant identification and classification play an important role in ecology, but the manual
process is cumbersome even for experimented taxonomists. Technological advances allows …

Sparse representation is an effective data classification algorithm that depends on the
known training samples to categorise the test sample. It has been widely used in various …

For representation based image classification methods, it is very important to well represent
the target image. As pixels at same positions of training samples and test samples of an …

In this paper, we deal with the descriptor combination problem in image classification tasks.
This problem refers to the definition of an appropriate combination of image content …

A rede LTE foi desenvolvida para prover comunicação entre terminais com aplicações de
voz, vídeo e dados com QoS (Qualidade de Serviço). Uma das maneiras para prover QoS é …