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Automatic Speech Recognition (ASR) System is defined as transformation of acoustic speech signals to string of words. This paper presents an approach of ASR system based on isolated word structure using Mel-Frequency Cepstral Coefficients (MFCC's), Dynamic Time Wrapping (DTW) and K-Nearest Neighbor (KNN) techniques. The Mel-Frequency scale used to capture the significant characteristics of the speech...
Handwriting has been known to be a very strong identifying characteristic of an individual and can be considered a behavioural biometric trait. This has made hand writer identification an important area of research. In this paper, a novel offline writer identification system is proposed using ensemble of multi-scale local ternary pattern histogram features. Features are extracted at multiple scales...
In this paper we present a novel image classification framework, which is able to automatically re-configure and adapt its feature-driven classifiers and improve its performance based on user interaction during on-line processing mode. Special emphasis is placed on the generic applicability of the framework to arbitrary surface inspection systems. The basic components of the framework include: recognition...
Diabetic retinopathy (DR) is one of the most important cause of vision loss in diabetic patients. The most primary sign of DR is the presence of exudates, and detecting these in early screening is crucial in preventing vision loss. This paper proposes a system for automatic exudate detection using a combination of texture features, extracted from different local binary pattern (LBP) variants, with...
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