We describe an approach to unsupervised high-accuracy recognition of the textual contents of an entire book using fully automatic mutual-entropy-based model adaptation. Given imag...
This paper presents results from analyzing the vulnerability of security-critical software applications to malicious threats and anomalous events using an automated fault injectio...
Artificial Neural Networks(ANNS) have top level of capability to progress the estimation of cracks in metal tubes. The aim of this paper is to propose an algorithm to identify mod...
Noise confounds present serious complications to accurate data analysis in functional magnetic resonance imaging (fMRI). Simply relying on contextual image information often resul...
The aging population and the growing amount of medical data have increased the need for automated tools in the neurology departments. Although the researchers have been developing ...