This paper will focus on the issue of human body dissimilarity detection from 3D bodyscan. A new 3D human body shape descriptor is proposed as well as a global geometric shape analysis of body shape surfaces coupled w...
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ISBN:
(纸本)9781479959341
This paper will focus on the issue of human body dissimilarity detection from 3D bodyscan. A new 3D human body shape descriptor is proposed as well as a global geometric shape analysis of body shape surfaces coupled with anthropometrics points. The aim of this research is then to establish a new methodology of human body morphology shapes detection in order to define the morphotypes of a given population. A computation of the geodesic distributions based on anthropometrics feature points for human torso provides quantitative information about their similarities. The Euclidean distance is the metric used for the comparison of the shape descriptors. The k-means clustering technique is then implemented to define the most relevant morphologies. Our methodology is then evaluated on 3D scan database of 53 female. The study may be attracted for further researchers from several research communities including patternrecognition, computer graphics, computer vision, anthropometry, human morphology, data analysis and mass customization.
Relevance of fuzzy logic, artificial neural networks, genetic algorithms and rough sets to patternrecognition and image processing problems is described through examples. Different integrations of these soft computin...
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ISBN:
(纸本)9812383433
Relevance of fuzzy logic, artificial neural networks, genetic algorithms and rough sets to patternrecognition and image processing problems is described through examples. Different integrations of these softcomputing tools are illustrated. Evolutionary rough fuzzy network which is based on modular principle is explained, as an example of integrating all the four tools for efficient classification and rule generation, with its various characterstics. An example of rough-fuzzy case generation is also provided. Significance of softcomputing approach in data mining and knowledge discovery is finally discussed along with the scope of future research.
This book constitutes the refereed proceedings of the internationalconference on softcomputing in Data Science, SCDS 2015, held in Putrajaya, Malaysia, in September *** 25 revised full papers presented were carefull...
ISBN:
(数字)9789812879363
ISBN:
(纸本)9789812879356
This book constitutes the refereed proceedings of the internationalconference on softcomputing in Data Science, SCDS 2015, held in Putrajaya, Malaysia, in September *** 25 revised full papers presented were carefully reviewed and selected from 69 submissions. The papers are organized in topical sections on data mining; fuzzy computing; evolutionary computing and optimization; patternrecognition; human machine interface; hybrid methods.
Our aim is to propose a new look at the dimensionality reduction in patternrecognition problems by extracting part of variables that are further called external context variables. We show how to incorporate them into...
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ISBN:
(纸本)9783642293467;9783642293474
Our aim is to propose a new look at the dimensionality reduction in patternrecognition problems by extracting part of variables that are further called external context variables. We show how to incorporate them into the Bayes classification scheme with loss functions that depend on class labels that are ordered. Then, the general form of the optimal context sensitive classifier is derived and the learning method that is based on kernel approximation is proposed.
We consider a multi-class patternrecognition problem with linearly ordered labels and a loss function, which measures absolute deviations of decisions from true classes. In the bayesian setting the optimal decision r...
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ISBN:
(纸本)9783540695721
We consider a multi-class patternrecognition problem with linearly ordered labels and a loss function, which measures absolute deviations of decisions from true classes. In the bayesian setting the optimal decision rule is shown to be the median of a posteriori class probabilities. Then, we propose three approaches to constructing an empirical decision rule, based on a learning sequence. Our starting point is the Parzen-Rosenblatt kernel density estimator. The second and the third approach are based on radial bases functions (RBF) nets estimators of class densities.
In this work, an efficient algorithm for face recognition using a local feature descriptor, Local Directional Number pattern (LDN) and softcomputing Technique, Adaptive Neuro-Fuzzy Inference Systems (ANFIS) is presen...
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ISBN:
(纸本)9781479939145
In this work, an efficient algorithm for face recognition using a local feature descriptor, Local Directional Number pattern (LDN) and softcomputing Technique, Adaptive Neuro-Fuzzy Inference Systems (ANFIS) is presented. Firstly, the face image is subjected to a Kirsch compass mask that gives the directional information of the image. With the help of masked output Local Directional Number pattern (LDN) code is computed. The LDN image is divided into several regions and the distribution of the LDN features is extracted from them. These features are then concatenated into a feature vector, which is used for ANFIS training and classification. The experimental evaluation of the presented method is carried out using Japanese Female Facial Expression Database (JAFFE) and Indian Face Database (IFD). The results obtained from the experiments prove that the presented method successfully recognize the faces under pose and facial expression variations.
Proceedings (12 reports) of the conference on Non-Conventional pattern Analysis in Remote Sensing are presented. The main topics discussed at the conference were following: neural networks for geographic information p...
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Proceedings (12 reports) of the conference on Non-Conventional pattern Analysis in Remote Sensing are presented. The main topics discussed at the conference were following: neural networks for geographic information processing;algorithms for supervised classification of remote sensing images;fuzzy logic and neural techniques integration;numeric and symbolic data fusion as an approach to remote sensing image analysis;incorporating mixed pixels in supervised classification development and an approach to fuzzy land cover mapping.
This review article provides a vast study on automated recognition of co-located patterns in video streaming. Traditionally numerous glitches such as face recognition, pattern or object recognition, scene understandin...
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ISBN:
(纸本)9781538695333
This review article provides a vast study on automated recognition of co-located patterns in video streaming. Traditionally numerous glitches such as face recognition, pattern or object recognition, scene understanding, co-located patternrecognition etc., have emerged through practices in patternrecognition domain. Our review study, purposes delivering an all-inclusive state-of-the-art review in the domain, and also discourses numerous encounters and trials in relation with its applications and its system. In this assessment, several applications are conversed in boundless aspect.
An attribute computing network induced by qualitative mapping is presented in this paper and the feedback adjustment mechanism for qualitative criterion and the learning algorithm are given. After that, the pattern re...
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ISBN:
(纸本)9781424425129
An attribute computing network induced by qualitative mapping is presented in this paper and the feedback adjustment mechanism for qualitative criterion and the learning algorithm are given. After that, the patternrecognition method based on the attribute computing network is brought forward. An actual application using such method is given in the end.
The two volumes set, CCIS 383 and 384, constitutes the refereed proceedings of the 14th internationalconference on Engineering Applications of Neural Networks, EANN 2013, held on Halkidiki, Greece, in September 2013....
ISBN:
(数字)9783642410130
ISBN:
(纸本)9783642410123;9783642410130
The two volumes set, CCIS 383 and 384, constitutes the refereed proceedings of the 14th internationalconference on Engineering Applications of Neural Networks, EANN 2013, held on Halkidiki, Greece, in September 2013. The 91 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers describe the applications of artificial neural networks and other softcomputing approaches to various fields such as patternrecognition-predictors, softcomputing applications, medical applications of AI, fuzzy inference, evolutionary algorithms, classification, learning and data mining, control techniques-aspects of AI evolution, image and video analysis, classification, patternrecognition, social media and community based governance, medical applications of AI-bioinformatics and learning.
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