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Search Results: 1 - 10 of 4719 matches for " recognition "
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Introduction
Gon?alo Marcelo
études Ricoeuriennes / Ricoeur Studies , 2011, DOI: 10.5195/errs.2011.70
Abstract: The guest editor introduces Vol. 2, no. 1 (2011).
A New Method for Chinese Character Strokes Recognition  [PDF]
Yan Xu, Xiangnian Huang, Huan Chen, Huizhu Jiang
Open Journal of Applied Sciences (OJAppS) , 2012, DOI: 10.4236/ojapps.2012.23027
Abstract: In this paper, the problem of stroke recognition has been studied, and the strategies and the algorithms related to the problem are proposed or developed. Based on studying some current methods for Chinese characters strokes recognition, a new method called combining trial is presented. The analysis and results of experiments showed that the method has the advantage of high degree of steadiness.
Are the Typologies Determined by the Post-Critical Belief Scale Predicted Well by the Religious Attitudes and Behaviour of Maltese Undergraduate Students?  [PDF]
Mary Anne Lauri, Josef Lauri, Joseph Borg
Psychology (PSYCH) , 2011, DOI: 10.4236/psych.2011.25063
Abstract: Religious beliefs play an important role in the study of religious practices and behaviour. Wulff (1997) suggested that there are four basic attitudes towards religion: Literal Affirmation, Literal Disaffirmation, Reductive Interpretation and Restorative Interpretation. Building on this work, Duriez, Soenans and Hutsebaut (2005) constructed the Post-Critical Belief Scale (PCBS). In their work, Duriez at al. conducted a Principal Component Analysis of the responses to this questionnaire. It yielded two factors which partitioned 2-dimensional space into four quadrants corresponding to the four types of beliefs postulated by Wulff (1997). The research question which is addressed in this paper is whether there is an association between scores on the PCBS and religious practices and behaviour in a staunchly Catholic country like Malta where over 98% are baptized in the Roman Catholic Church. This question was addressed by administering a questionnaire to a random sample of 650 students at the University of Malta, of which 421 completed the questionnaire. Of those who answered the questionnaire, 349 were undergraduates. The questionnaire consisted of a number of questions about religious attitudes and behaviour, and also included the PCBS. The analysis of the association between membership of one of the four belief typologies and the participants’ responses to other questions related to religious beliefs, religious practice and sexual norms was carried out using Discriminant Analysis. The results indicate that, at least in this sample of Maltese university students, these three measures do a reasonably good job in identifying membership in three of Wulff’s four belief typologies.
Complex Object Shapes Recognition. Automatic Aid Photointerpretation in a Satellite Image  [PDF]
Macho Anani, Kada Mouedden, Youcef Amar, Sara Lebid, Mohammed Benyahia
International Journal of Geosciences (IJG) , 2012, DOI: 10.4236/ijg.2012.31003
Abstract: The interpretation of geological structures on earth observation images involves like many other domains to both visual observation as well as specialized knowledge. To help this process and make it more objective, we propose a method to extract the components of complex shapes with a geological significance. Thus, remote sensing allows the production of digital recordings reflecting the objects’ brightness measures on the soil. These recordings are often presented as images and ready to be computer automatically processed. The numerical techniques used exploit the morphology ma- thematical transformations properties. Presentation shows the operations’ sequences with tailored properties. The example shown is a portion of an anticline fraction in which the organization shows clearly oriented entities. The results are obtained by a procedure with an interest in the geological reasoning: it is the extraction of entities involved in the observed structure and the exploration of the main direction of a set of objects striking the structure. Extraction of elementary entities is made by their physical and physiognomic characteristics recognition such as reflectance, the shadow effect, size, shape or orientation. The resulting image must then be stripped frequently of many artifacts. Another sequence has been developed to minimize the noise due to the direct identification of physical measures contained in the image. Data from different spectral bands are first filtered by an operator of grayscale morphology to remove high frequency spatial components. The image then obtained in the treatment that follows is therefore more compact and closer to the needs of the geologist. The search for significant overall direction comes from interception measures sampling a rotation from 0 to 180 degrees. The results obtained show a clear geological significance of the organization of the extracted objects.
A Feasible Approach for Automatic Detection and Recognition of the Bengalese Finch Songnotes and Their Sequences  [PDF]
Khan Md. Mahfuzus Salam, Tetsuro Nishino, Kazutoshi Sasahara, Miki Takahasi, Kazuo Okanoya
Journal of Intelligent Learning Systems and Applications (JILSA) , 2010, DOI: 10.4236/jilsa.2010.24025
Abstract: The Bengalese finch song has been widely studied for its unique features and similarity to human language. For com-putational analysis the songs must be represented in songnote sequences. An automated approach for this purpose is highly desired since manual processing makes human annotation cumbersome, and human annotation is very heu-ristic and easily lacks objectivity. In this paper, we propose a new approach for automatic detection and recognition of the songnote sequences via image processing. The proposed method is based on human recognition process to visually identify the patterns in a sonogram image. The songnotes of the Bengalese finch are dependent on the birds and similar pattern does not exist in two different birds. Considering this constraint, our experiments on real birdsong data of different Bengalese finch show high accuracy rates for automatic detection and recognition of the songnotes. These results indicate that the proposed approach is feasible and generalized for any Bengalese finch songs.
Text Independent Automatic Speaker Recognition System Using Mel-Frequency Cepstrum Coefficient and Gaussian Mixture Models  [PDF]
Alfredo Maesa, Fabio Garzia, Michele Scarpiniti, Roberto Cusani
Journal of Information Security (JIS) , 2012, DOI: 10.4236/jis.2012.34041
Abstract: The aim of this paper is to show the accuracy and time results of a text independent automatic speaker recognition (ASR) system, based on Mel-Frequency Cepstrum Coefficients (MFCC) and Gaussian Mixture Models (GMM), in order to develop a security control access gate. 450 speakers were randomly extracted from the Voxforge.org audio database, their utterances have been improved using spectral subtraction, then MFCC were extracted and these coefficients were statistically analyzed by GMM in order to build each profile. For each speaker two different speech files were used: the first one to build the profile database, the second one to test the system performance. The accuracy achieved by the proposed approach is greater than 96% and the time spent for a single test run, implemented in Matlab language, is about 2 seconds on a common PC.
Libyan Licenses Plate Recognition Using Template Matching Method  [PDF]
Alla A. El. Senoussi Abdella
Journal of Computer and Communications (JCC) , 2016, DOI: 10.4236/jcc.2016.47009
Abstract: License plate recognition (LPR) applies image processing and character recognition technology to identify vehicles by automatically reading their license plates. The work presented in this paper aims to create a computer vision system capable of taking real-time input image from a static camera and identifying the license plate from extracted image. This problem is examined in two stages: First the license plate region detection and extraction from background and plate segmentation to sub-images, and second the character recognition stage. The method used for the license plate region detection is based on the assumption that the license plate area is a high concentration of smaller details, making it a region of high intensity of edges. The Sobel filter and their vertical and horizontal projections are used to identify the plate region. The result of testing this stage was an accuracy of 67.5%. The final stage of the LPR system is optical character recognition (OCR). The method adopted for this stage is based on template matching using correlation. Testing the performance of OCR resulted in an overall recognition rate of 87.76%.
Semi-Automatic Objects Recognition in Urban Areas Based on Fuzzy Logic  [PDF]
Federico Prandi, Raffaella Brumana, Francesco Fassi
Journal of Geographic Information System (JGIS) , 2010, DOI: 10.4236/jgis.2010.22011
Abstract: Three dimensional object extraction and recognition (OER) from geographic data has been definitely one of more important topic in photogrammetry for quite a long time. Today, the capability of rapid generating high-density DSM increases the supply of geographic information but the discrete nature of the measuring makes more difficult to recognize correctly and to extract 3D objects from these surface. The proposed methodology wants to semi-automate some geographic objects clustering operations, in order to perform the recognition process. The clustering is a subjective process; the same set of data items often needs to be partitioned differently based on the application. Fuzzy logic gives the possibility to use in a mathematical process the uncertain information typical of human reasoning. The concept at the base of our proposal is to use the information contained in Image Matching or LiDAR DSM, and typically understood by the human operator, in a fuzzy recognition process able to combine the different input in order to perform the classification. So the object recognition approach proposed in our workflow integrates 3D structural descriptive components of objects, extracted from DSM, into a fuzzy reasoning process in order to exploit more fully all available information, which can contribute to the extraction and recognition process and, to handling the object’s vagueness. The recognition algorithm has been tested with to different data set and different objectives. An important issue is to apply the typical human process which allows to recognize objects in a range image in a fuzzy reasoning process. The investigations presented here have given a first demonstration of the capability of this approach.
Memory Strength and Criterion Shift in the False Memory Paradigm: A Learning Case  [PDF]
Shahid Naved, Ameer Haider Ali, Khubaib Ahmed Qureshi
Psychology (PSYCH) , 2011, DOI: 10.4236/psych.2011.23033
Abstract: The attempt has been made to investigate the criterion shift hypothesis once again by re-evaluating the confi-dence measurement, which will possibly clarify the role that criterion shifts play in the false memory phenome-non (recollection of an event, or the details of an event, that did not occur). Literature review shows that this hypothesis still needs research upon the same topic. The study was experimental in which students of Hamdard University were selected as subjects - 40 students from BBA and MBA programs. Both male/female and left/right handed subjects participated. All the subjects were not native English speakers. The experiment was conducted using a computer program to collect the data. The experiment had two parts, firstly a study/recall phase and secondly a test/recognition phase. The scale we introduced to allow participants to assess their own certainty about the classification of recognition items is more detailed than that used in the Roediger and McDermott study. Our hypothesis was that a shift in decision criterion would become evident by means of a lower certainty measure for lure words as compared to target words from the lists. This difference was found in our data. The mean certainty measure we found for the critical lures is significantly lower than the mean cer-tainty for the targets.
English Sentence Recognition Based on HMM and Clustering  [PDF]
Xinguang Li, Jiahua Chen, Zhenjiang Li
American Journal of Computational Mathematics (AJCM) , 2013, DOI: 10.4236/ajcm.2013.31005
Abstract:

For English sentences with a large amount of feature data and complex pronunciation changes contrast to words, there are more problems existing in Hidden Markov Model (HMM), such as the computational complexity of the Viterbi algorithm and mixed Gaussian distribution probability. This article explores the segment-mean algorithm for dimensionality reduction of speech feature parameters, the clustering cross-grouping algorithm and the HMM grouping algorithm, which are proposed for the implementation of the speaker-independent English sentence recognition system based on HMM and clustering. The experimental result shows that, compared with the single HMM, it improves not only the recognition rate but also the recognition speed of the system.

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