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Roller element bearing fault diagnosis is crucial in industry to maintain that the machine is in good condition so that there is no delay of work due to machine breakdown. This paper discusses the use of Extreme Learning Machine (ELM) algorithm to classify bearing faults. The performance of ELM is compared with Back Propagation (BP) algorithm. It was found that the results show that the ELM has smaller...
The success of machine learning (ML) algorithms depends on the quality of data given to them. If the input data contains insufficient or irrelevant features, the accuracy of machine learning algorithm decreases. Attribute selection has a key role in creation of classification models. Based on the ‘logic behind the inference’ principle in the Nyaya school of thought, this paper proposes a new method...
In this paper, we proposed an optimum combination of sub-band power features method for improving the classification accuracy rate of left- or right-hand movement imagery electroencephalogram signals. The sub-band power features were extracted from the best time segment of electroencephalogram trials and the proposed training model determined the optimum combination of sub-bands. Our approach was...
We present a low-complexity framework for classifying elementary arm movements (reach retrieve, lift cup to mouth, and rotate arm) using wrist-worn inertial sensors. We propose that this methodology could be used as a clinical tool to assess rehabilitation progress in neurodegenerative pathologies tracking occurrence of specific movements performed by patients with their paretic arm. Movements performed...
Optical Character Recognition can be defined as the process of detecting and identifying text from a scanned image. There are a number of techniques by which recognition is carried out in several languages. The main steps of optical character recognition are Line segmentation, Word segmentation, Character segmentation and Character recognition. Character recognition has two phases: Feature extraction...
Face recognition system is used for the identification and verification of a face from a video or digital image. In the first phase, Viola Jones algorithm is used to detect and crop face region automatically from image/video frame. The second phase is to recognize the face of a person, in our proposed method Bag of Word technique used to extract features from an image which uses SURF for interest...
The main objective of the spatial image classification is to extract information classes from a multiband raster spatial image. The network structure and number of inputs are the key factors in deciding the performance and accuracy of the traditional pixel based image classification techniques like Support Vector Machines (SVM), Artificial Neural Networks (ANN), Fuzzy logic, Decision Trees (DT) and...
Tiny target detections, especially power line detection, have received great attention due to its critical role in ensuring the flight safety of low-flying unmanned aerial vehicles (UAVs). In this paper, an accurate and robust power line detection method is proposed, wherein background noise is mitigated by an embedded convolution neural network (CNN) classifier before conducting the final power line...
As different staining patterns of HEp-2 cells indicate different diseases, the classification of Indirect Immune Fluorescence (IIF) images on Human Epithelial-2 (HEp-2) cell is important for clinical applications. Different from traditional pattern recognition techniques, we use CNN to extract more high-level features for cell images classification. Compared to the existing CNN based HEp-2 classification...
As of today, diagnosis of ADHD is highly dependent on subjective observations, which has motivated researchers to investigate quantitative methods for the discrimination of ADHD and Non-ADHD subjects using EEG data. The goal of the effort reported here is to classify subjects with high accuracy, as well as to do so based on a select few channels. By making use of AR model features, several classifiers...
The proposed method aims to detect brain abnormality using bilateral symmetry property about the interhemispheric fissure (IHF) of human head scans. MRI brain has structural symmetry between the right cerebral hemisphere (RCH) and left cerebral hemisphere (LCH) of brain cerebrum. Any brain abnormalities due to tumors, hemorrhage, etc disturbs the similarity between the two hemispheres. We split the...
Speech impaired people are detached from the mainstream society due to the lacking of proper communication aid. Sign language is the primary means of communication for them which normal people do not understand. In order to facilitate the conversation conversion of sign language to audio is very necessary. This paper aims at conversion of sign language to speech so that disabled people have their...
Brain-Computer Interface (BCI) is a direct communication pathway between brain and external devices bypassing the natural pathway of nerves and muscles. BCI enables an individual to send commands to a peripheral device using his brain activity. Electroencephalogram (EEG) is the most commonly used brain signal acquisition method as it is simple, economical and portable. Feasibility of detecting familiar...
Diabetes, referred to as diabetes mellitus, describes a group of metabolic diseases in which the person has high blood glucose. Possible complications that can be caused by badly controlled diabetes: Eye complications, Foot complication, Skin complications, Heart problems, Hypertension, etc. Diabetic retinopathy (DR), a common complication of diabetes, affects the blood vessels in the retina. It is...
This paper presents a classification method for multi-class classification of electromyography (EMG) signals from eight hand movements. The data were collected from 15 subjects. The EMG signals were extracted using 16 time-domain feature extraction methods. The 16 features are reduced using principal component analysis (PCA) to enhance the classification accuracy. The features results from PCA are...
The human brain, which receives input from the sensory organs and sends output to the muscles, is the command center of the nervous system. There are various kinds of brain monitoring techniques including computed tomography, magnetic resonance imaging (MRI), positron emission tomography, functional MRI, electroencephalography (EEG) and magnetoencephalography. Among those of techniques EEG is the...
The genetic traits in the Electroencephalogram (EEG), has made it a possible characteristic for the continuous biometric human verification. It is important for a biometric characteristic to have an acceptable performance on large populations besides satisfying the main requirements of a biometric system such as uniqueness, universality, acceptability, permanence, collectability, circumvention and...
Software development today is riddled with various challenges, and hangs on the balance of cost and profit. The industry is yearning for shorter times to market without any reduction in quality. Since component based software engineering emerged as a prominent and solid approach to alleviate these challenges, the question remains are there any benefits of employing this paradigm in other areas, excluding...
Image classification using kernels have very great importance in remote sensing data. The goal of this work is to efficiently classify the large set of aerial images into different classes. This paper introduces a kernel based classification for aerial images. It uses Grand Unified Regularized Least Square (GURLS) and library for support vector machines (LIBSVM). This paper compares the performance...
In most document archiving systems, one of the main fields is to identify the category of documents. In most case, determination of the document category in archiving tasks requires the application of classification model, which have had successes in improving documents processing. However, concerns exploding the frequency of use of documents in many office managers have driven increasing interests...
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