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This article presents to detect lung tumor, classification and area recognition system. Nowadays, Lung tumor is major cause of death for all the people. Early detection of lung tumor plays an important part to enhance chance for survive to live. Early detecting of tumor is a important role for the treatment where Computed Tomography (CT) screening are consider as appropriate method for detecting the...
The data shows that about 20% of car failures come from the rear axle of the car. Accordingly we use a support vector machine based on optimization algorithm of Drosophila melanogaster as the fault diagnosis method. The vibration signal is denoised by double-tree complex wavelet transform. The feature extraction is performed by wavelet packet decomposition, and the extracted feature vector is taken...
In this paper, we propose to achieve the classification of pathologic voices and essentially the classification between organic pathologies: it's about polyp, edema and nodule pathologies using new features. The principle contribution in this work is to provide new parameter more efficient than the classic MFCC. It's about calculating MFCC not from the speech signal but from the speech multiscale...
Speech uttered by the human beings contains the information about speakers, languages and contents. Language of uttered speech can easily be identified by extracting the language specific information from it. Identification of language of speech is known as Language Identification (LID). Identification of language from speech is helpful in its translation, speech recognition and speech activated automatic...
Many operators are working in jobs that require stressful mental tasks such as transportation supervision, vehicle driving, banking and others. Prevention of fatigued-based human error, that has been a standing challenge in such work areas, can be detected and quantified using human performance level. This paper proposes an enhanced method for operator fatigue detection based on computer-keyboard...
Texture classification is a problem that has variousapplications such as remote sensing and forest speciesrecogni- tion. Solutions tend to be custom fit to the datasetused but fails to generalize. The Convolutional NeuralNetwork (CNN) in combination with Support Vector Machine(SVM) form a robust selection between powerful invariantfeature extractor and accurate classifier. The fusion ofexperts provides...
The motivation behind the research on overlapping speech has always been dominated by the need to model human-machine interaction for dialog systems and conversation analysis. To have more complex insights of the interlocutors' intentions behind the interaction, we need to understand the type of overlaps. Overlapping speech signals the interlocutor's intention to grab the floor. This act could be...
Face liveness verification is an important procedure against fraud for many applications of face recognition. In this paper, a face liveness verification method based on hyper-spectrum analysis is proposed. Based on the hyperspectral face images collected by a hyperspectral camera, the spectral characteristics of real human faces and face photos in various lighting conditions and feature positions...
Machine learning algorithms are useful for decision making on valuable datasets which are using in emerging fields such as networks, medical and e-governance. Ensemble classifier is a most useful approach which is the combination of classification algorithms for performing effective classification in machine learning. Even though, the selection of ensemble is becoming very difficult task for the specific...
This paper deals with Optical character recognition (OCR) for Odia handwritten Characters which deserves more attention from the researchers. In the proposed method, an existing database has been studied. First of all the images are preprocessed. Then the preprocessed images are used for feature extraction. Features are extracted using two simple yet powerful algorithms like shadow feature algorithm...
This paper presents a novel technique of image classification using BOVW model. The entire process first involves feature detection of images using FAST, the choice made in order to speed up the process of detection. Then comes the stage of feature extraction for which FREAK, a binary feature descriptor is employed. K-means clustering is then applied in order to make the bag of visual words. Every...
A CAD system for diagnosing the mammograms is proposed in this work. The mammogram image is preprocessed using adaptive median filter and ROI is segmented using otsu's thresholding technique. Then the extracted GLCM features from ROI were given to the classifier. The classifiers such as SVM and KNN were used in this CAD system and the performance metrics were analyzed. The classification accuracy...
Helitron is considered as very important type of DNA involved in mechanism's evolution. These elements are not well studied and the major researches done are biological experiments. In this paper, we propose a novel approach aiming to characterize and classify helitron's types. Accordingly, we use the Support Vector Machine (SVM) classification technique known to be preferment in DNA related studies...
Aim /Objective: To find an optimum image restoration and classification algorithm for identifying the defects in industrial applications. Methodology: A master dataset for industrial applications has been developed for defect identification and the acquired data is further applied to Non-Local Means algorithm for denoising and image restoration and the restored image is further applied with feature...
Over the years, the growth in medical image processing is increasing in a tremendous manner. The rate of increasing diseases with respect to various types of cancer and other related human problems paves the way for the development in biomedical research. Thus processing and analyzing these medical images is of high importance for clinical diagnosis. This work focuses on performing effective classification...
In recent years, the computer vision and intelligent video surveillance technology have been significantly developed, thanks to the development of computer science. The automated scenario pedestrian intrusion detection has been widely used in more and more fields, such as security. In this paper, we focus on the research work of dynamic pedestrian intrusion detection, improving some shortcomings in...
In this paper, we have proposed an apnea frame detection method based on the Empirical Mode Decomposition(EMD) of wavelet reconstructed delta wave of EEG signal. The method begins with wavelet transforming an EEG frame and reconstructing the low frequency delta wave from the approximate coefficients. EMD is carried on the reconstructed delta wave to generate intrinsic mode functions(IMF). Mean rate...
In the field of Human Computer Interaction (HCI), human emotion recognition from speech signal is evolving as a recent research area. Speech is the most common way for communication among human beings. Speech consists of sentences, which can be further segregated into words. Words consist of phonemes which are considered to be the primary voice construction elements. This paper presents a classification...
Brain Functional Networks (BFNs), graph theoretical models of brain activity data, provide a systems perspective of complex functional connectivity within the brain. Neurological disorders are known to have basis in abnormal functional activities that could be captured in terms of network markers. Schizophrenia is a pathological condition characterized with altered brain functional state. We created...
In this paper, we aim to study the problem of 3D face recognition. This problem becomes complex when we consider the human face expressions and different face occlusions. In this context is situated our work, we use the 3D UMB database to evaluate two powerful methods: the 3D Local Binary Pattern (3D-LBP) and the 3D Grey Level Co-occurrence Matrix (3D-GLCM). We tested also the combination of these...
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