Weakly supervised semantic segmentation with only image-level labels aims to reduce annotation costs for the task. Existing approaches generally leverage class activation maps (CAMs) locate object regions pseudo label generation. However, CAMs can discover most discriminative parts of objects, thus leading inferior pixel-level labels. To address this issue, we propose a saliency guided I...

In symptomatic subjects, the reliability of tests for shoulder joint range of motion has yet to be determined. For this reason, inter-rater and intra-rater agreement trials were undertaken to ascertain the reliability of visual estimation, goniometry, still photography, "stand and reach" and hand behind back reach for six different shoulder movements. Intra-class correlation coefficients (Rho) ...

Recognition rate of characters in the handwritten is still a big challenge for the research because of a shape variation, scale and format in a given handwritten character. A more complicated handwritten character recognition system needs a better feature extraction technique that deal with such variation of hand writing. In other hand, to obtain efficient and accurate recognition rely on off-l...

Blind source separation is a common processing tool to analyse the constitution of pixels of hyperspectral images. Such methods usually suppose that pure pixel spectra (endmembers) are the same in all the image for each class of materials. In the framework of remote sensing, such an assumption is no more valid in the presence of intra-class variabilities due to illumination conditions, weatheri...

Introduction: Measuring the size of motor evoked potentials (MEPs) induced by transcranial magnetic stimulation (TMS) is an investigational technique to show the level of corticospinal excitability however, some of the fundamental methodological aspects of TMS (such as the effects of inter-pulse intervals (IPI) on MEP size) are not fully understood, this issue raises concerns about the re...

Feature selection plays an important role in algorithms for processing high-dimensional data. Traditional pattern classification and information theory methods are widely applied to feature methods. However, traditional such as Fisher Score, Laplacian relief use class labels inadequately. Previous based MIFS ignore the intra-class tight inter-class sparse property of samples. To address these p...