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This paper aims at the classification of hand gestures using electromyographic signals (EMG) obtained through a MyoTM armband, which has eight medical grade electrodes. Each electrode provides information regarding muscles contraction performed during the execution of the movement. From these electrodes signals are extracted seven features for each one of eight electrodes. After extraction of the...
The typical method of entering a password for user authentication is vulnerable to hacking; therefore, various security technologies using bio-signals, such as iris scan, electrocardiography, electromyography (EMG), and fingerprint recognition, are being developed. In this research, an authentication algorithm using an EMG signal is proposed to supplement the weakness of personal certification techniques...
An application of artificial vision and artificial neural networks techniques in face recognition, is presented. In order to do that, a set of images (frontal face photos) with different lighting conditions, gestures, accessories and distances is used. A stepwise algorithm allows to achieve a satisfactory results, obtaining the correct identification of images inside and outside the data set.
Many areas include public transportation, hospitals and shopping mall use the computer technologies for security reasons. The need for integrating the technology with human needs is increased dramatically. Car license plate recognition is one of those technologies that help people to secure themselves from different attacks either attacks that affect their lives or their properties. There is an increasing...
Plant recognition from their leaves has become a popular area in the machine learning and image processing. In this study 7 different types of apricot trees were determined and classified by using their leaves. At first leaves images were pre-processed. After than each image was scanned by 5×5 overlapping filter and median values of each filter process were recorded to represent the leaves. After...
In most big cities, firearm assault is a common crime. Some state of the art research aim to recognize firearms once they were fired. However, to prevent this type of criminal behavior it is necessary to detect firearms in real time, before they are fired, and maintaining at minimum false alarms. In this paper, we propose a method to detect hand guns by using its shape and real dimensions. The proposed...
Convolutional neural network (CNN) is more and more important in pattern recognition. In this work, we adopt label relations and long short-term memory (LSTM) to develop an accurate CNN-based scene classification algorithm. Traditional scene classification algorithms assume that labels are mutually exclusive. However, this is not reasonable when an image has a variety of objects and hence has multiple...
In this study, classification of 11 different Power Quality (PQ) disturbances with Artificial Neural Networks (ANN) has been done by using the attributes obtained with S-Transform. It was aimed to achieve accurate and high classification performance in noisy environment by using the least number of attributes representing PQ disturbances. The most suitable ones from the attributes were selected by...
In this study, classification of Normal and Extra systolic heart sounds (HS) have been carried out using in PASCAL Heart Sounds (HS) data base. The extrasystole is the HS that is produced by performing an extra beat in each heart cycle, unlike the heartbeat normal cycle. It can be felt by people as palpitations. Occurrence of these sounds in certain age groups may be the indication of tachycardia...
High impedance faults are not easy to be measured and detected by convetional relay protection. This paper proposed simualtions studies for detection high impedance fault in extra high voltage transmission line (EVT). The fault simulations based on simplified 2 diodes model. Current signal from the measurement is processed using discrete wavelet transform type haar wavelet to obtain coefficient detail...
This work present new parameters based on biometrie handwritten information for the writer identification. The feature extraction is developed by new algorithms based on image processing techniques. The handwritten parameters will be classified by artificial neural network and fusion strategy in order to increase the accuracy. After experiments, and using a dataset composed by 100 writers, this proposal...
Aiming at maintaining the accuracy of grasping pattern recognition meanwhile evaluating the required force, this paper uses Linear discriminant analysis (LDA) to realize pattern recognition and artificial neural networks to establish the relationship between surface EMG signals and fingertip force in each grasping mode. Once the grasping pattern identified, the program calls the corresponding force...
As the technique that determines the position of a target device based on wireless measurements, Wi-Fi localization is attracting increasing attention due to its numerous applications and the widespread deployment of Wi-Fi infrastructure. In this paper, we propose ConFi, the first convolutional neural network (CNN)-based Wi-Fi localization algorithm. Channel state information (CSI), which contains...
Human Epithelial type-2 (HEp-2) cells are used as substrates for the detection of Anti Nuclear Antibodies (ANA) in the Indirect Immunofluorescence (IIF) test to diagnose autoimmune diseases. Pathologists in the laboratory examine the IIF slides to detect and recognize theHEp-2 cell patterns to generate the report. So, the IIF test is subjective and requires objective analysis. This paper introduces...
Myoelectric pattern recognition (MPR) can be used for intuitive control of virtual and robotic effectors in clinical applications such as prosthetic limbs and the treatment of phantom limb pain. The conventional approach is to feed classifiers with descriptive electromyographic (EMG) features that represent the aimed movements. The complexity and consequently classification accuracy of MPR is highly...
The Cloud Gaming model emerges with the evolution of the Cloud Computing and communication technologies. Through smartphones, PCs, tablets, consoles and other devices, people can access and use games on demand via data streaming, regardless the computing power of these devices. The Internet is the fundamental way of communication between the device and the game, which is hosted on a environment known...
The present work is part of the “Hand of Hope” project, which seeks to develop low-cost robotic prostheses with the aim of contributing to the social and labor inclusion of people with motor disabilities of their upper extremities. The specific objective to address in this work is the design and development of the system architecture to recognition of EMG (Electromyography) signal patterns, the purpose...
Language or pattern recognition is an ever-growing field in research. The motivation behind this work is the growing importance of foreign languages in everyday life. It is specifically focused on groups who might have to face a foreign language somewhere and can't seem to understand it. This will also be beneficial for partially visually impaired persons. It will help in recognizing the alphabets...
This paper presents a novel method that investigates the use of Paraconsistent Artificial Neural Network (PANN) and upper-limb electromyography signals for classification of movements, due to their intrinsic ability to deal with imprecise, inconsistent and paracomplete data. The preliminary study presents promising results in terms of processing time and accuracy. The average classification accuracy...
Vehicle analysis is an important task in many intelligent applications, which involves vehicle-type classification(VTC), license-plate recognition(LPR) and vehicle make and model recognition(MMR). Among these tasks, MMR plays an important complementary role with respect to LPR. In this paper, we propose a novel framework to detect moving vehicle and MMR using convolutional neural networks. The frontal...
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