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A plethora of disorders are found in human oral mucosa. A variety and huge number of lesions and diseases in human oral mucosa have been clinically identified and classified. Most lesions have the possibility to develop into oral cancer. The initial diagnosis of oral cancer is to inspect the ocular regions carefully and register the oral cavity of the patient as true-color digital images. The decision...
Good speaker recognition systems should identify the speaker irrespective of what is spoken, including non-speech sounds that are often produced during natural conversations. In this work, the inclusion of breath sounds in the training phase of the speaker recognition is analyzed using the popular Gaussian mixture model-universal background model (GMM-UBM) and deep neural network (DNN) based systems...
In the arena of biomedical engineering, the classification and analysis of epilepsy from Electroencephalography (EEG) signals forms an important area of research. When the neurons get hyper excited, seizures occur causing a lot of inconvenience and trouble to the patient. For the study of the predominant abnormalities in the cerebral cortex of the brain, EEG is used widely. Due to the long nature...
Next to stroke, the epilepsy is one of the most serious neurological disorders. Due to the hyperactive firing of neurons on a cellular level, epilepsy is caused. The activities of the cortical regions are recorded with the help of Electroencephalogram (EEG) which helps in the diagnosis of epilepsy. The normal patterns of the activities of neurons becomes severely disturbed in the case of epilepsy,...
Use of the error correcting codes (ECC) in a multiclass audio emotion recognition problem is proposed to improve the emotion recognition accuracy. We visualize the emotion recognition system as a noisy communication channel, thus motivating the use of ECC. We assume the emotion recognition process consists of an audio feature extractor followed by an artificial neural network (ANN) for emotion classification...
Open Source Software's (OSS) have been existing since decades. Several organizations around the globe are joining the notion to build with Open Source Model. They are finding open source as an attractive and practical alternative to proprietary software. Price tag of Open Source Software is very appealing. It can be inspected, modified, and freely redistributed. So several major organizations are...
For automatic screening of eye diseases, it is very important to segment regions corresponding to the different eye-parts from the fundal images. A challenging task, in this context, is to segment the network of blood vessels. The blood vessel network runs all along the fundal image, varying in density and fineness of structure. Besides, changes in illumination, color and pathology also add to the...
The directional antenna technology in wireless mesh network is used improve the spatial reuse of the wireless channel, where nodes communicate simultaneously without interference of each other. A Technology require to meet customer demands and improve the performance in WLAN 802.11. Wireless is a scalable, reliable and cost effective technology which can be used to implement 802.11 for utility maximization...
The aim of this paper is to give a performance analysis by considering the advantage of Code Converters as a feature extraction technique and Sparse Representation Classifier (SRC) as a post classifier for the classification of the epilepsy risk levels obtained from Electroencephalography (EEG) signals. A group of related or similar disorders which is generally characterized by the occurrence of frequency...
The basic goal of this work is to develop a Consonant-Vowel Recognition System (CVRS) for determining a sequence of Consonant-Vowel (CV) units present in a given speech utterance. In this work, we are focusing on developing CVRSs for Indian languages namely Bengali and Odia. This framework of developing CVRSs can be extended to any Indian languages. We have developed two separate CVRSs for Bengali...
Continuous density hidden Markov models (CD-HMMs) are doubly stochastic processes which are extensively used in speech and image signal processing. Especially in case of isolated spoken word recognition systems, the spoken words are usually modeled using HMMs. While CD-HMMs are in extensive use, to most of the speech community the HMMs remain abstract in the sense there has been no nice way of visualizing...
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