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.
According to the ‘salt and pepper’ effect of pixel-based multi-feature classification and over-smoothing of ground details of object-based image analysis, in this paper, an approach, which fuses pixel-based features and multi-scale object-based features is proposed to improve the accuracy of image classification. (1) Firstly, mean shift algorithm is used to segment the image to obtain over-segmentation...
To date, there are no reliable markers for making an early diagnosis of schizophrenia before clinical diagnostic criteria are fully met. Neuroimaging and pattern classification techniques are promising tools towards predicting transition to schizophrenia. Here, we investigated the diagnostic performance of a combination of neuroanatomical and clinical data in predicting transition to schizophrenia...
When using SVM to solve practical problems, the selection of the kernel function and its parameters plays a vital role on the results of good or bad, and only need to select the appropriate kernel function and parameters to get a SVM classifier with good generalization ability. RBF kernel function gets the most widely used, and there are only two parameters, which are the C and γ. This paper discusses...
In this era of flexible manufacturing systems, increase in demand of automatic and unattended machining process is very high. Thus arise the need for proper online tool condition monitoring methods, in order to minimize error and waste of work-material. In this study, Support Vector Machine (SVM), Artificial Neural Network (ANN) and Bayes classifier are used to develop such a system for automatic...
The objective of this paper is to estimate the joint angle and the force from a moving elbow joint based on the SEMG. An AdaBoost with SVM-based compoment classifier is proposed to discriminate different movements based on SEMG of the forearm. Then, the average integral EMG(AIEMG) variables collecting by an EMG measurement device is introduced to estimating joint angles. Through the estimated joint...
In this paper, we propose an algorithm called SVM-WKNN for precisely indoor positioning, which can be applied to intelligent robot and wireless sensor network to achieve great performance. The key issue of indoor positioning is how to use the instable wireless network and nonlinear wireless signal strengths to accurately locate the position of a person or object. However, the traditional linear methods,...
Facial expressions convey human emotions as a simple and effective non-verbal communication method. Motivated by this special characteristic, facial expression recognition rapidly gains attention in social computing fields, especially in Human Computer Interaction (HCI). Identifying the optimal set of facial emotion markers is an important technique that not only reduces the feature vector dimensionality,...
The classification performance of Support Vector Machine (SVM) is heavily influenced by its kernel parameter g and penalty factor c. in this paper, Cross-validation (CV) based grid-search optimization, CV-based genetic algorithm (GA) and CV-based particle swarm optimization (PSO) are respectively used for parameters optimization in SVM for fault classification of inverters in traction converter. Simulation...
Speech signal processing and its recognition system have gained a lot of attention from last few years due to its widespread application. In this study, we have conducted a comparative analysis for effective detection of Parkinson's disease using various machine learning classifiers from voice disorder known as dysphonia. To investigate robust detection process, three independent classifier topologies...
The automatic traffic sign detection and recognition has been converted to a real challenge for high performance of computer vision and machine learning techniques. It is an important issue, in particular for vehicle safety applications. It is usually tackled in three stages: detection, feature extraction and classification. We focus in this work on the second stage of the process, namely traffic...
Drowsiness is one of the main causes of severe traffic accidents occurring in our daily life. In order to reduce the number of drowsiness-induced accidents, various researches have been conducted with the aim of finding practical and non-invasive drowsiness detection systems by using behavioral measuring techniques. Many of the previous works on behavioral measuring techniques have mainly focused...
This paper presents application of texture analysis using gray-level co-occurrence matrix (GLCM) for segmentation of oil palm area based on WorldView-2 imagery data. Different parameters of GLCM consisting of five distance spacing and three directions will be calculated, where eight texture features will be extracted. Based on land-use categories determined in WorldView-2 image, the features for oil...
We explore the application of Kernel Support Vector Machines (SVM) to the realm of text messages. Our intent is to classify the author of a text message based on usage patterns present in a training set of text messages. We achieve between 57% and 96% accuracy in determining the author of unknown samples.
In this paper, classifying and indexing video genres using Support Vector Machines (SVMs) are based on only audio features. In fact, those segmentation parameters are extracted at block levels, which have a major benefit by capturing local temporal information. The main contribution of our study is to present a powerful combination between the two employed audio descriptors Mel Frequency Cepstral...
Steganography is the art of hiding the secretmessages in an innocent medium like images, audio, video, text, etc. such that the existence of any secret message is notrevealed. There are various steganography tools available. In this paper, we are considering three algorithms - nsF5, PQ,Outguess. To compare the robustness and to withstand the steganalytic attack of the above three algorithms, an algorithm...
Highly accurate predictions of load demand and photovoltaic (PV) output have become possible in recent years because of improved measuring instruments and the increase of databases on load demand and PV output. The appropriate control parameters for actual power system operation can be determined by using these predictions. Although parameters determined by conventional methods are accurate, they...
Medical image processing is an interdisciplinary field that has been attracted by various fields such as applied mathematics, computer science and engineering, biology and medicine etc. Due to the development of technologies in imaging modalities, more challenges arise, how to process and analyze a huge volume of images for the diagnosis of diseases and treatment procedure. In this Support Vector...
Directivity, as a characteristic parameter of electromagnetic radiation source, could be used to classify different radiation sources, and the ESD events could be considered as typical sources. The parameter could be measured by electric field intensity radiating in all directions in the space. In this paper, we would build three basic antenna models which are all working at 3GHz and set cube receiving...
Activity recognition datasets are generally imbalanced, meaning certain activities occur more frequently than others. Not incorporating this class imbalance results in an evaluation that may lead to disastrous consequences for elderly persons. In this work, we evaluate various types of resampling methods: at algorithmic level using CS-SVM and at data level using SMOTE-CSVM and OS-CSVM combined with...
Drivers not being cautious enough is one of the major reasons for many of today's fatal road accidents. Drivers being fatigued or distracted have been identified as the main two reasons behind drivers losing their attention. PERCLOS and gaze estimation are two visual cue based parameters which can be used to estimate driver drowsiness and distraction respectively. This paper describes advanced and...
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.