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.
This study proposes a visual approach for classification of multivariate data based on the enhanced separation feature of a visual technique, called Hypothesis-Oriented Verification and Validation by Visualization (HOV3). In this approach, the user first builds up a visual classifier from a training dataset based on its data projection plotted by HOV3 with a statistical measurement of the training...
Spectral classification for hyperspectral image is a challenging job because of the number of spectral in a hyperspectral image and high dimensional spectral. In this paper, we proposed a method to enhance the spectral classification using the Adaboost for hyperspectral image analysis. By applying the Adaboost algorithm to the classifier, the classification can be executed iteratively by giving weight...
In this paper we present a novel and robust algorithm for automatic recognition of road signs by using histogram of oriented gradient (HOG) as the main feature and minimum distance classifier (MDC) to classify numbers written on speed limit road signs. It also describes how other geometrical properties can be added to feature vector in order to increase the robustness of proposed algorithm.
Facial expression analysis is one of the popular fields of research in human computer interaction (HCI). It has several applications in next generation user interfaces, human emotion analysis, behavior and cognitive modeling. In this paper, a facial expression classification algorithm is proposed which uses Haar classifier for face detection purpose, Local Binary Patterns(LBP) histogram of different...
Failure bitmaps of manufactured memory arrays may contain the information of some systematic defects and have hence been used to monitor the process and to improve the memory yield. It is important to have an accurate flow to classify the memory failure bitmap signatures. The memory bitmap signature classification can be either dictionary based or machine learning based. This paper introduces a hybrid...
Harmful text information filtering is a typical pattern recognition problem of small sample, the prediction result of classifier was biased towards the class with more samples, because of the samples that including the harmful information were difficult to gain. Construct virtual samples is an effective means to solve the problem of pattern recognition in the small sample, using the up-sampling method...
The automatic insertion of diacritics in electronic texts is necessary for a number of languages, including French, Romanian, Croatian, Sindhi, Vietnamese, etc. When diacritics are removed from a word and the resulting string of characters is not a word, it is easy to recover the diacritics. However, sometimes the resulting string is also a word, possibly with different grammatical properties or a...
The prediction result of classifier is biased towards the class with more samples, when the harmful text information is filtered. This is because that the samples that including the harmful information were difficult to gain. Construct virtual samples is an effective means to solve the problem of pattern recognition in the small sample, using the up-sampling method to construct virtual samples in...
Speech affective recognition is an important branch of speech recognition, whose main purpose is the emotional characteristics included in the analysis of speech signals. Because the use of a single model to identify which identify significant limitations. This paper presents a recognition model based on HMM and PNN, which using PNN for classification and using HMM for generating feature matching...
In this work we propose Inclusive vector to keep the key words available in natural language database. The inclusive vectors are generated by the process of extraction of words given in the source and the cited items of records published in the ISI Thompson Citation Indexes. The proposed inclusive vector exhibits related words and the degree of their relationships. In this work we present the results...
The research presented in this paper refers to classification of geometric shapes (cubes, pyramids and cylinders) using multilayer neural network. The input data of the algorithm are the images of shapes placed in different positions and distances from the camera. The classification is based on feature vectors that are obtained using methods of digital image processing. Feature vectors are inputs...
One approach for deaf signs recognition and classification is presented in the paper. It is assumed that the signs are presented in digital images. Recognition algorithm is consisted of several stages. At the beginning it is necessary to perform appropriate image processing in sense of segmentation and filtration of the input images. Aim is to detect arm position, i.e. sign of interest. For this purpose...
Support vector machine approach is an effective technique to solve poly-dimensional outlier detection, which can avoid the curse of dimensionality problem and has higher accuracy. One-class support vector machine-based outlier detection techniques take advantage of spatial and temporal correlations that exist between sensor data to cooperatively identify outliers. However, for large scale training...
Mouse dynamics is the process of identifying individual users based on their mouse operating behaviors. Many classification algorithms have been proposed for checking users' identity, thus it is natural to ask how well each classifier performs and how various classifiers compare to each other (e.g., to identify promising research directions). Unfortunately, we cannot conduct a valid comparison of...
The paper presents an innovative hierarchical classification model which should be applied for large-scale biometric identification systems, in order to improve their performance. The model is relying on a multi-level fusion approach, but completed with a feature-selection strategy. The practical application of the proposed model concerns networks security issues, especially for databases remote access,...
A model of probabilistic neural network (PNN) to classify the loess according to its collapsibility is suggested in this paper, in which five physical property indexes such as water content, dry density, void ratio, saturation degree and plastic liquid are taken as input neural cells and the output neural cell is coefficient of collapsibility. 76 groups of sample to be trained under different smoothing...
Pedestrian detection is a major difficulty in the field of object detection. In order to achieve a balance between speed and accuracy, we propose a new framework in pedestrian detection based on HOG-PCA and Gentle AdaBoost. Firstly, each block-based feature of the image is encoded using the histograms of oriented gradients (HOG), then Principal Components Analysis (PCA) is used to reduce the dimensions...
Emergence of Web 2.0, internet users can share their contents with other users using social networks. In this paper microbloggers' contents are evaluated with respect to how they reflect their categories. Migrobloggers' category information, which is one of the four categories that are economy sport, entertainment or technology, is taken from wefollow.com application. 2105 RSS news feeds, whose category...
Reject inference is a term that distinguishes attempts to correct models in view of the characteristics of rejected applicants. The main difficulty in establishing reject inference model is that the ¡®through-the-door' applicant population is unavailable. In this paper, we propose a hybrid data mining technique for reject inference. It is a three-stage approach: k-means cluster, support vector machines...
Different conditions, such as occlusions, changes of lighting, shadows and rotations, make vehicle type classification still a challenging task, especially for real-time applications. Most existing methods rely on presumptions on certain conditions, such as lighting conditions and special camera settings. However, these presumptions usually do not work for applications in real world. In this paper,...
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.