The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The frequent occurrence of road congestion and traffic accidents has affected people's travel efficiency and travel safety. Traffic sign recognition has become one of the key research objects in intelligent transportation system. This paper studies the identification of road traffic signs based on video images. First of all, collected image will be image preprocessing with image reduction, brightness...
The current focus of our research is to detect and classify the plant disease in agricultural domain, by implementing image processing techniques. We aim to propose an innovative set of statistical texture features for classification of plant diseases images of leaves. The input images are taken by various mobile cameras. The Scale-invariant feature transform (SIFT) features used as texture feature...
In the person re-identification across multiple camera research field, attributes of the pedestrian are important cues to differentiate the appearance of each identity. In this work, ten types of attributes are considered as defined in the DukeMTMC-attribute dataset. A custom deep network architecture is proposed to perform the identification process. Furthermore, experiments were carried out to assess...
The death of the patients is an important event in the intensive care unit (ICU), mortality risk prediction thus offers much information for clinical decision making. However, Patient ICU mortality prediction faces challenges in many aspects, such as high dimensionality, imbalance distribution. In this paper, we modified the cost-sensitive principal component analysis (CSPCA), which is denoted by...
This paper introduces a new system to identify handwritten signatures. For feature generation, we propose the Histogram of templates, while the Artificial Immune recognition System (AIRS) is used to achieve the identification task. A writer-independent strategy is proposed to train the AIRS to get an open system that can identify any new writer. Experiments are conducted on a benchmark dataset composed...
In this paper, we try to recognize negative emotions (sadness and disgust) of human affecting driving by using physiological signals that are commonly used to deal with human emotions. To do this, emotional stimuli are used to induce sadness and disgust, and emotion recognition is performed based on the feature vector extracted from the physiological signals collected on the induced emotion by a stimulus...
Sensors in industrial systems fault frequently leading to serious consequences regarding cost and safety. The authors propose support vector machine-based classifier with diverse time- and frequency-domain feature models to detect and classify these faults. Three different kernels, i.e., linear, polynomial, and radial-basis function, are employed separately to examine classifier's performance in each...
Recognition of epileptic seizures is an important issue and in certain circumstances it is desirable to have portable equipment implementing the algorithm in order to better monitor the patients. This work considers a widely used EEG database from University of Bonn as reference for comparing our recognition method with other previously reported. In order to perform epileptic seizures we combine a...
One-class support vector machines (OCSVM) have been recently applied to detect anomalies in wireless sensor networks (WSNs). Typically, OCSVM is kernelized by radial bais functions (RBF, or Gausian kernel) whereas selecting Gaussian kernel hyperparameter is based upon availability of anomalies, which is rarely applicable in practice. This article investigates the application of OCSVM to detect anomalies...
This paper presents a support vector machine (SVM) based model predictive control (MPC) strategy to manage the engine speed to the set-point of idle speed. The predictive model is trained by SVM due to its accuracy of learning nonlinear process, simple training program and no over-fitting nature. To reduce the computational burden of controller and retain the dynamic information of system, the instantaneous...
The present status of heart sound recognition is introduced in the paper. In order to improve the performance of heart sound recognition, a new model based on SVM is proposed. Firstly, the wavelet transform is used to reduce the noise of the heart sound, and then MFCC feature is extracted from heart sound. On this basis, the Support Vector Machine is used to build the classification model. In the...
At present, shallow characteristics are usually utilized to represent the distributed features of text for Chinese spam classification, causing the problem of inexact text vector representation and low classification performance. A novel Chinese spam classification method based on weighted distributed feature is proposed by combining the features of TF-IDF weighted algorithm with the distributed text-based...
For face recognition systems, impostors can obtain legal identity authentication by presenting the printed images, the downloaded images or candid videos to the sensor. In this paper, an enhanced face local binary feature (ELBP) of a face map is extracted as a classification feature to identify whether the face map is a real face or a fake face. Compared with the dynamic or static methods proposed...
The modular multilevel converter with series and parallel connectivity was shown to provide advantages in several industrial applications. Its reliability largely depends on the absence of failures in the power semiconductors. We propose and analyze a fault-diagnosis technique to identify shorted switches based on features generated through wavelet transform of the converter output and subsequent...
In view of the support vector machine (SVM) model applied in vibrant fault diagnosis for hydro-turbine generating unit, it exists problems of parameter settings and classification-plane incline due to unequal sample, which leads to lower diagnosis accuracy. As a new bionic intelligent optimization algorithm for glowworm swarm optimization(GSO), it has the characteristics of strong versatility and...
Acoustic event detection (AED) is currently a very active research area with multiple applications in the development of smart acoustic spaces. In this context, the advances brought by Internet of Things (IoT) platforms where multiple distributed microphones are available have also contributed to this interest. In such scenarios, the use of data fusion techniques merging information from several sensors...
A Brain-Computer Interface (BCI) speller system based on the Steady-State Visually Evoked Potentials (SSVEP) paradigm is presented. The potentials are elicited through the gaze fixation at one out of the four checkerboards shown on screen, which are flickering at 5, 12, 15 and 20 Hz. After the feature extraction, two dimensionality reduction algorithms, Principal Components Analysis (PCA) and Linear...
The emergence of medical social media has made it possible for more and more patients to share their views and experiences on the medical care platform. These subjective texts contains patients' evaluation information for doctors and can be analyzed to provide rich decision-making information for patients and hospitals. Therefore, we propose a LSTM (Long Short Term Memory) based text sentiment classification...
Despite widespread use of commercial anti-virus products, the number of malicious files detected on home and corporate computers continues to increase at a significant rate. Recently, anti-virus companies have started investing in machine learning solutions to augment signatures manually designed by analysts. A malicious file's determination is often represented as a hierarchical structure consisting...
SVM (Support Vector Machine), a state of the art classifier model is implemented on a computational mobile platform and its performances are evaluated against a low complexity classifier such as SFSVC (Super Fast Vector Support Classifier) on the same platform. For a better comparison, similar implementation for the two architectures are considered, such as using the same basic linear algebra library...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.