Parser plays a very important role in computational linguistics. In this paper, here we describe a parsing technique for Bangla grammar recognition. the parser is, by nature, a shift reduce parser and constructs a par...
详细信息
ISBN:
(纸本)9781509012695
Parser plays a very important role in computational linguistics. In this paper, here we describe a parsing technique for Bangla grammar recognition. the parser is, by nature, a shift reduce parser and constructs a parse table based on LR strategy. It takes the Context Free Grammar (CFG) of the Bangla language as input and constructs parser table from the grammar. the parse table is visited on bottom-up approach. this parser is free from the problem of the left factoring and left recursion. To avoid the inflection (BIVOKTI) of Bangla we describe a new approach. Hence only the main form of the Bangla word is stored in the repository. Our experiment shows that the scheme can detect all forms of Bangla sentences even for nontraditional forms.
In a multi-lingual country like India, a document page may contain more than one script form. Under the three-language formula, the document may be printed in English, Devnagari and one of the other official Indian la...
the problem of text recognition is becoming increasingly important due to the active introduction of digital computing and the widespread use of word processors. patternrecognition is one of the most difficult from a...
详细信息
the problem of text recognition is becoming increasingly important due to the active introduction of digital computing and the widespread use of word processors. patternrecognition is one of the most difficult from a mathematical point of view and one of the most popular areas of artificial intelligence programming. In the work is researched approaches and methods of solving text recognition problem, improved the performance of the available algorithms for text recognition and created algorithmic software. According to the analysis, neural networks were selected for handwriting recognition. the main advantage of using neural networks is a good generalization ability, the ability to use context analysis and recognize a symbol based on the surrounding symbols. the software implementation features of Hopfield and convolutional neural network, genetic algorithm, which were chosen as effective methods for recognizing handwritten text, were considered. Algorithmic software and web application that uses these methods for the task of handwritten text recognition is developed.
Automation of the image shearing measurement technique applied to optical fibre geometry is discussed. the use of both edge detection filters and a multi-layer perceptron neural network to identify the critical 'j...
详细信息
Automation of the image shearing measurement technique applied to optical fibre geometry is discussed. the use of both edge detection filters and a multi-layer perceptron neural network to identify the critical 'just touch' condition are compared. the repeatability of cladding diameter measurements using both methods are presented which demonstrate the superiority of the neural network technique.
A motion-based, correspondence-free technique for human gait recognition in monocular video is presented. We contend that the planar dynamics of a walking person are encoded in a 2D plot consisting of the pairwise ima...
详细信息
ISBN:
(纸本)0769516025
A motion-based, correspondence-free technique for human gait recognition in monocular video is presented. We contend that the planar dynamics of a walking person are encoded in a 2D plot consisting of the pairwise image similarities of the sequence of images of the person, and that gait recognition can be achieved via standard pattern classification of these plots. We use background modelling to track the person for a number of frames and extract a sequence of segmented images of the person. the self-similarity plot is computed via correlation of each pair of images in this sequence, For recognition, the method applies Principal Component Analysis to reduce the dimensionality of the plots, then uses the k-nearest neighbor rule in this reduced space to classify an unknown person. this method is robust to tracking and segmentation errors, and to variation in clothing and background. It is also invariant to small changes in camera viewpoint and walking speed. the method is tested on outdoor sequences of 44 people with 4 sequences of each taken on two different days, and achieves a classification rate of 77%. It is also tested on indoor sequences of 7 people walking on a treadmill, taken from 8 different viewpoints and on 7 different days. A classification rate of 78% is obtained for near-fronto-parallel views, and 65% on average over all view.
In this paper we present an innovative approach to speech understanding which is based on a fine-grained knowledge representation automatically compiled from a semantic network and on iterative optimization. Besides a...
详细信息
Considering the Particle Swam Optimization (PSO) is easily relapsing into local extremum, an improved PSO(IPSO) is proposed in this paper. In the new algorithm, we apply the evolution speed factor as the trigger condi...
详细信息
ISBN:
(纸本)9781467317443
Considering the Particle Swam Optimization (PSO) is easily relapsing into local extremum, an improved PSO(IPSO) is proposed in this paper. In the new algorithm, we apply the evolution speed factor as the trigger conditions to stochastically disturb the local optimal solution. the IPSO algorithm can not only improve extraordinarily the convergence velocity in the evolutionary optimization, but also can adjust the balance between global and local exploration suitably. then a speaker recognition approach using this improved algorithm to train Support vector machine (SVM) is presented. the experimental results show that the SVM optimized by IPSO achieves higher classification accuracy than the standard SVM and effectively improves the speaker identification speed and accuracy.
this paper presents an overview of an artificial neural network (ANN) based partial discharge (PD) distribution patternrecognition problem to power system application. After referring briefly to the developments of A...
详细信息
this paper presents an overview of an artificial neural network (ANN) based partial discharge (PD) distribution patternrecognition problem to power system application. After referring briefly to the developments of ANN technique-based PD measurements, the paper outlines how the introduction of new emerging technology has resulted in the design of a number of PD diagnostic systems for practical application in test laboratories and on site. the structure of a PD data base and selection of learning of PD data pattern, extraction of relevant characteristic feature or information for PD recognition are discussed. Some practical problems encountered in the neuro-fuzzy techniques based real time PD recognition are also addressed.
the benchmark of a chaotic patternrecognition (PR) system is the following: First of all, one must be able to train the system with a set of "training" patterns. Subsequently, as long as there is no testing...
详细信息
Images are important element in our daily life. We use images to identify things or associate them with others that become important in decision making or correlate with other object for identification purpose. Featur...
详细信息
ISBN:
(纸本)9781538662885
Images are important element in our daily life. We use images to identify things or associate them with others that become important in decision making or correlate with other object for identification purpose. Feature extraction need to be applied to images for them to be useful for the mentioned purpose. By definition, feature extraction is the transformation of input data into a set of features, normally distinctive properties of input patterns that differentiate between many input of patterns. It is also the process to represent raw image (important criteria or parts of) to help in decision making such as pattern detection, classification, recognition or image processing or machine learning. the process of extracting information from images is one of the important elements in authenticating process of biometric system. Many techniques for extracting features have been emerging in the current research. LBP (Local Binary pattern) has been a popular technique in biometric systems used for feature extraction. LBP is a texture feature ex fraction method which produce clearer image result. Another favorite technique known as SVD (Single Value Decomposition) has been selected, discussed and compared withthe latter. A sample of still color images were tested for both methods and the results are compared and discussed further in here. this paper concentrates on these two techniques for image processing in a biometric system.
暂无评论