We investigate the effect of quantified statistical facial asymmetry as a biometric under expression variations. Our findings show that the facial asymmetry measures (AsymFaces) are computation ally feasible, containi...
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ISBN:
(纸本)0769516025
We investigate the effect of quantified statistical facial asymmetry as a biometric under expression variations. Our findings show that the facial asymmetry measures (AsymFaces) are computation ally feasible, containing discriminative information and providing synergy when combined with Fisherface and Eigen-face methods on image data of two publically available face databases (Cohn-Kanade and Feret).
In this study, we critically analyse and compare performances of several global optimization (GO) approaches with our hybrid GLPτS method, which uses meta-heuristic rules and a local search in the final stage of find...
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ISBN:
(纸本)9781605580463
In this study, we critically analyse and compare performances of several global optimization (GO) approaches with our hybrid GLPτS method, which uses meta-heuristic rules and a local search in the final stage of finding a global solution. We also critically investigate a Stochastic Genetic Algorithm (StGA) method to demonstrate that there are some loopholes in its algorithm and assumptions. Subsequently, we employ the GLPτS method for neural network (NN) supervised learning, when using our intelligent system for solving real-world patternrecognition and classification problem. In the preprocessing data phase, our system also uses Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) for dimensionality reduction and minimization of the chosen number of features for the classification problem. Finally, the reported results are compared with Backpropagation (BP) to demonstrate the competitive properties and the efficiency of our system. Copyright 2008 ACM.
the proceedings contain 12 papers. the special focus in this conference is on Physiological Computing Systems. the topics include: A data-driven model based on support vector machine to identify chronic hypertensive a...
ISBN:
(纸本)9783030279493
the proceedings contain 12 papers. the special focus in this conference is on Physiological Computing Systems. the topics include: A data-driven model based on support vector machine to identify chronic hypertensive and diabetic patients;inner flower: Design and evaluation of a tangible biofeedback for relaxation;towards industrial assistance systems: Experiences of applying multi-sensor fusion in harsh environments;preface;Development and assessment of a self-paced BCI-VR paradigm using multimodal stimulation and adaptive performance;Hand gesture recognition based on EMG data: A convolutional neural network approach;heart rhythm qualitative analysis using low-cost and open source electrocardiography: A study based on atrial fibrillation detection;integrating biocybernetic adaptation in virtual reality training concentration and calmness in target shooting;bio-behavioral modeling of workload and performance;simple and robust automatic detection and recognition of human movement patterns in tasks of different complexity.
When the dimension N of the input vector is much larger than the number M of different training patterns to be learned, a one-layered, hard-limited perceptron with N input nodes and P neurons (P > equals Log2M)...
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ISBN:
(纸本)0819415472
When the dimension N of the input vector is much larger than the number M of different training patterns to be learned, a one-layered, hard-limited perceptron with N input nodes and P neurons (P > equals Log2M) is generally sufficient to accomplish the learning- recognition task. the recognition should be very robust and very fast if an optimum noniterative learning scheme is applied to the perceptron learning process. this paper concentrates at the discussion of two special characteristics of this novel patternrecognition system: the automatic feature extraction and the automatic feature competition. An unedited video movie recorded on a series of learning-recognition experiments may demonstrate these characteristics of the novel system in real time.
Speech recognition techniques for Arabic language are still in its infant stage and gain much attention recently. this is due to Arabic as the language of the Holy book of Muslims;hence it has attracted attention of n...
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ISBN:
(纸本)9781467367134
Speech recognition techniques for Arabic language are still in its infant stage and gain much attention recently. this is due to Arabic as the language of the Holy book of Muslims;hence it has attracted attention of native speakers and other Muslims who are non-native Arabic speakers as they need to use Arabic language while performing worships. therefore, this research investigated Arabic phonemes recognition specifically for Malay speakers. the proposed methods are evaluated and examined utilizing a corpus which contains Arabic phoneme tokens with Mel Frequency Cepstral Coefficients (MFCC) as feature extraction. Next, recognition process is attained using Dynamic Time Warping (DTW) and patternrecognition Neural Network (PRNN) for verifying the similarity between the Arabic phonemes. In this study, three methods are used to evaluate the recognition stage. Firstly, DTW and PRNN are evaluated solely followed by combination of both. Results attained showed that the overall recognition rate of this method is 89.92% for DTW individually, 94% for PRNN solely whilst for fusion of DTW and PRNN the recognition rate attained is 98.28% and thus proven that fusion of DTW and PRNN can be utilised for recognition of Arabic phonemes.
this paper represents the different techniques used for the study of robust facial recognition. the need of facial recognition is expanding very rapidly in current technologies as it is possible to identify a humane f...
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Interactions between proteins and ligands are relevant in many biological processes. In the last years, such interactions have gained even more attention as the comprehension of protein-ligand molecular recognition is...
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ISBN:
(纸本)9781509038343
Interactions between proteins and ligands are relevant in many biological processes. In the last years, such interactions have gained even more attention as the comprehension of protein-ligand molecular recognition is an important step to ligand prediction, target identificantion, and drug design, among others. this article presents GReMLIN (Graph Mining strategy to infer protein-Ligand INteraction patterns), a strategy to search for conserved protein-ligand interactions in a set of related proteins, based on frequent subgraph mining, that is able to perceive structural arrangements relevant for protein-ligand interaction. When compared to experimentally determined interactions, our in silico strategy was able to find many of relevant binding site residues/atoms for CDK2 and active site residues/atoms for Ricin.
作者:
Betts, TomSchool of Art
Design and Architecture University of Huddersfield Queensgate Huddersfield HD1 3DH United Kingdom
this paper will examine the relationship of patternrecognition and Gestalt principles to procedural form in gameplay. It will identify key features of pattern based play mechanics and outline important synergies betw...
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Automatic recognition of modulated signals has seen increasing demand nowadays. the use of artificial neural networks (NNs) for the purpose has been popular since the late 90's. this paper proposes radial basis fu...
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ISBN:
(纸本)0769519571
Automatic recognition of modulated signals has seen increasing demand nowadays. the use of artificial neural networks (NNs) for the purpose has been popular since the late 90's. this paper proposes radial basis functions (RBF) to perform the recognition of eight kinds of modulated signals. Design considerations for the NN recognition are discussed. Computer simulation results show that the overall success rate is over 93% at the signal-to-noise ratio (SNR) of 6 dB, and the overall success rate is over 96% at the SNR of 10 dB.
this paper proposes an automatic recognition scheme for hand printed Bangla (an Indian script) numerals using neural network models. A Topology Adaptive Self Organizing Neural Network is first used to extract from a n...
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