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检索条件"任意字段=5th International Conference on Pattern Recognition in Bioinformatics"

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Facial Asymmetry quantification for expression invariant human identification

Facial Asymmetry quantification for expression invariant hum...

引用

5th IEEE international conference on Automatic Face and Gesture recognition

作者： Liu, Y Schmidt, KL Cohn, JF Weaver, RL Carnegie Mellon Univ Inst Robot Pittsburgh PA 15213 USA

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).

关键词： pattern recognition

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Intelligent hybrid system for pattern recognition and classification 08

Intelligent hybrid system for pattern recognition and classi...

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5th international conference on Soft Computing As Transdisciplinary Science and Technology, CSTST '08

作者： Jordanov, Ivan Georgieva, Antoniya School of Computing University of Portsmouth Portsmouth PO1 3HE United Kingdom Nuffield Department of Obstetrics and Gynaecology University of Oxford Oxford OX3 9DU United Kingdom

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 pattern recognition 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.

关键词： Global optimization

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3rd international conference on Physiological Computing Systems, PhyCS 2016, 4th international conference on Physiological Computing Systems, PhyCS 2017 and 5th international conference on Physiological Computing Systems, PhyCS 2018

3rd International Conference on Physiological Computing Syst...

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3rd international conference on Physiological Computing Systems, PhyCS 2016, 4th international conference on Physiological Computing Systems, PhyCS 2017 and 5th international conference on Physiological Computing Systems, PhyCS 2018

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.

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AUTOMATIC FEATURE-EXTRACTION AND FEATURE COMPETITION IN A PERCEPTRON pattern RECOGNIZER 5

AUTOMATIC FEATURE-EXTRACTION AND FEATURE COMPETITION IN A PE...

引用

5th international conference on Applications of Artificial Neural Networks

作者： HU, CLJ SO ILLINOIS UNIV DEPT ELECT ENGNCARBONDALEIL 62901

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 pattern recognition 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.

关键词： Feature extraction Video pattern recognition Analog electronics Astatine Electrical engineering Neurons Visualization Binary data Promethium

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Investigation of Dynamic Time Warping and Neural Network for Arabic Phonemes recognition Based Malay Speakers 5

Investigation of Dynamic Time Warping and Neural Network for...

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IEEE international conference on System Engineering and Technology (ICSET)

作者： Almisreb, Ali Abd Abidin, Ahmad Farid Tahir, Nooritawati Md Univ Teknol MARA UiTM Fac Elect Engn Shah Alam 40450 Selangor Malaysia

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 pattern recognition 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.

关键词： Arabic Language Mel Frequency Cepstral Coefficients Dynamic Time Warping pattern recognition Neural Network Malay

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Study of robust facial recognition under occlusion using different techniques 5

Study of robust facial recognition under occlusion using dif...

引用

5th international conference on Intelligent Computing and Control Systems, ICICCS 2021

作者： Jayant, Deepanshu Bhat, Aruna Delhi Technological University Department of Computer Science New Delhi India

ISBN: (纸本)9781665412728

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 face features through different digital mediums. Although, facial recognition is not done achieved easily in the real-world situation as most of the time the human face goes through various occlusions making hard for the system to complete the identification process. the sole purpose of this article is to compare the techniques used and identify the most accurate and efficient one from all of them. Robust facial recognition is a task of doing recognition under uncertain environments and features. the main aim of the robust facial recognition is to analyze and identify the face images where the picture proposes difficult viewpoints, angles, poses, illumination, noises and expressions. the techniques studied for this article are Local Binary patterns, HOG features, Occlusion-adaptive Deep Networks (ODN), Robust Principal Component Analysis (RPCA), Progressive Convolutional Neural Network and Region Attention Networks (RAN). In this article, a table is created summarizing the experiments and results of the techniques studied. © 2021 IEEE.

关键词： Local binary pattern

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GReMLIN: A graph mining strategy to infer protein-ligand interaction patterns 16

GReMLIN: A graph mining strategy to infer protein-ligand int...

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16th IEEE international conference on bioinformatics and Bioengineering (BIBE)

作者： Santana, Charles A. Cerqueira, Fabio R. da Silveira, Carlos H. Fassio, Alexandre V. de Melo-Minardi, Raquel C. Silveira, Sabrina de A. Univ Fed Vicosa Dept Comp Sci BR-36570900 Vicosa MG Brazil Univ Fed Itajuba Itabira Adv Campus Itabira Brazil Univ Fed Minas Gerais BR-31270901 Belo Horizonte MG Brazil

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.

关键词： graph interaction protein ligand pattern

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pattern recognition: Gameplay as negotiating procedural form

Pattern recognition: Gameplay as negotiating procedural form

引用

5th international conference on Digital Research Association: think Design Play, DiGRA 2011

作者： Betts, Tom School of Art Design and Architecture University of Huddersfield Queensgate Huddersfield HD1 3DH United Kingdom

this paper will examine the relationship of pattern recognition and Gestalt principles to procedural form in gameplay. It will identify key features of pattern based play mechanics and outline important synergies between programming paradigms and procedural form. In the course of the paper I will examine the formal and aesthetic qualities of procedural structures and discuss how they generate the experience of psychological flow. I will also identify the role of these mechanisms and their effects in current game design. © 2011 Authors & Digital Games Research Association DiGRA.

关键词： Computer games

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Neural network application in automatic recognition of communication signals 5

Neural network application in automatic recognition of commu...

引用

5th international conference on Computational Intelligence and Multimedia Applications

作者： Chen, J Kuo, YH Li, JD Fu, FL Xidian Univ Sch Commun Engn Xian 710071 Shanxi Peoples R China

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.

关键词： signal processing radial basis function networks neural nets noise telecommunication signalling pattern recognition neural network application automatic recognition communication signal recognition artificial neural network radial basis function RBF modulated signal NN recognition signal-to-noise ratio SNR

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recognition of handprinted bangla numerals using neural network models 5th

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5th international conference on Asian Fuzzy Systems Society, AFSS 2002

作者： Bhattacharya, U. Das, T.K. Datta, A. Parui, S.K. Chaudhuri, B.B. Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B. T. Road Calcutta35 India Computer and Statistical Service Center Indian Statistical Institute 203 B. T. Road Calcutta35 India

ISBN: (纸本)9783540431503

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 numeral pattern a skeletal shape that is represented as a graph. Certain features like loops, junctions etc. present in the graph are considered to classify a numeral into a smaller group. If the group is a singleton, the recognition is done. Otherwise, multilayer perceptron networks are used to classify different numerals uniquely. the system is trained using a sample data set of 1880 numerals and we obtained 90.56% correct recognition rate on a test set of another 3440 samples. the proposed scheme is sufficiently robust with respect to considerable object noise. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Neural network models

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