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On the topological properties of intuitionistic fuzzy rough sets

On the topological properties of intuitionistic fuzzy rough ...

引用

IEEE international conference on Granular computing (GRC)

作者： Renbing Lin Jiyi Wang Department of Mathematics &Physics Zhejiang Shuren University Hangzhou China School of Mathematics and Information Science Zhejiang Normal University ZJNU Jinhua Zhejiang China

This paper is devoted to the discussion of the relationship between intuitionistic fuzzy rough set models and intuitionistic fuzzy topologies on a finite universe. The IFT Condition for intuitionistic fuzzy topology is proposed. It is proved that the set of all lower approximation sets based on a reflexive and transitive intuitionistic fuzzy relation consists of a intuitionistic fuzzy topology which satisfies IFT Condition.

关键词： Fuzzy sets Rough sets Topology Set theory Fuzzy set theory Physics Information science pattern analysis pattern recognition

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Transactions on Computational Science XXIII 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： Marina L. Gavrilova C. J. Kenneth Tan Xiaoyang Mao Lichan Hong

ISBN: (数字)9783662437902

ISBN: (纸本)9783662437896

This, the 23rd issue of the Transactions on Computational Science journal, guest edited by Xiaoyang Mao and Lichan Hong, is devoted to the topic of security in virtual worlds. It contains extended versions of the best papers selected from those presented at the international conference on Cyberworlds 2013, held at Keio University, Yokohama, Japan, October 21-23, 2013. The 11 papers in the volume have been organized into topical sections on modeling, rendering, motion, virtual environments and affective computing.

关键词： Theory of Computation Information Systems and Communication Service Computer Imaging, Vision, pattern recognition and Graphics Simulation and Modeling Artificial Intelligence

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Estimation of camera pose using 2D to 3D corner correspondence

Estimation of camera pose using 2D to 3D corner corresponden...

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international conference on Information Technology: Coding and computing (ITCC)

作者： Fanhuai Shi Yuncai Liu Inst. of Image Processing & Pattern Recognition Shanghai Jiaotong University China

ISBN: (纸本)0769521088

We present a new method for the determination of camera pose from 2D to 3D corner correspondence. Two cases are considered: the orthogonal corner and the general corner with known space angles. The contribution of the paper is in two folds: one is that the camera pose parameters, i.e., the rotation and translation, are easily recovered from a 2D to 3D corner correspondence; the other is that experiments using both simulated data and real images are conducted, which present good results.

关键词： Cameras Robot vision systems Aircraft navigation Image processing pattern recognition Image edge detection Image motion analysis Robot kinematics Orbital robotics Calibration

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pattern recognition system based on decision trees and fuzzy logic: Anti-HIV molecules application

Pattern recognition system based on decision trees and fuzzy...

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IEEE international conference on Multimedia computing and Systems (ICMCS)

作者： Mohamed Kissi Mohammed Ramdani Driss Cherqaoui Department de Mathematiques et Informatique Faculté des Sciences El Jadida Morocco Department d'informatique (LIM@II) Faculté des Sciences et Techniques Mohammedia Morocco Department de chimie Faculté des Sciences Semlalia Marrakech Morocco

Several works structure activity relationship (SAR) of anti-HIV molecules (Human Immunodeficiency Virus) were studied by different statistical methods and non-linear models (neural networks). But few studies have used the heuristic methods. In this work, we are interested to study this relationship by fuzzy logic and decision trees. The resulting model explain SAR with only tow rules described by three of 7 molecular descriptors. This rules generalize the 79 compounds studied. Decision trees show good performance in the learning and prediction phases.

关键词： pattern recognition Decision trees Fuzzy logic Human immunodeficiency virus Statistical analysis Artificial neural networks Testing Neural networks Chemical compounds Linear regression

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Scale Space and Variational Methods in Computer Vision 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Luca Calatroni Marco Donatelli Serena Morigi Marco Prato Matteo Santacesaria

ISBN: (数字)9783031319754

ISBN: (纸本)9783031319747

This book constitutes the proceedings of the 9th international conference on Scale Space and Variational Methods in Computer Vision, SSVM 2023, which took place in Santa Margherita di Pula, Italy, in May 2023.;The 57 papers presented in this volume were carefully reviewed and selected from 72 submissions. They were organized in topical sections as follows: Inverse Problems in Imaging; Machine and Deep Learning in Imaging; Optimization for Imaging: Theory and Methods; Scale Space, PDEs, Flow, Motion and Registration.

关键词： Image Processing and Computer Vision Computer Communication Networks Computer Applications Machine Learning Mathematics of computing pattern recognition

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FTRA 8th international conference on Multimedia and Ubiquitous Engineering, MUE 2014

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FTRA 8th international conference on Multimedia and Ubiquitous Engineering, MUE 2014

ISBN: (纸本)9783642548994

The proceedings contain 67 papers. The special focus in this conference is on Multimedia and Ubiquitous Engineering. The topics include: 3D mapping of garment patches based on human body section loop data;a robust hand tracking approach based on modified tracking-learning-detection algorithm;a new heuristic algorithm for improving total completion time in grid computing;optimization problems related to Hamiltonian paths;selecting processes supported by fuzzy calculations;a network delay jitter smoothing algorithm in cyber-physical systems;a novel activity recognition approach based on mobile phone;indoor pedestrian navigation with shoe-mounted inertial sensors;hardware based distributive power migration and management algorithm for cloud environment;generic distributed sensing in support of context awareness in ambient assisted living;an embedded control system designed based on soft PLC;novel protocols of modulation level selection in decode-and-forward multinode cooperative communication systems;fair spectrum allocation with reducing spectrum handoff in cognitive radio sensor networks;an empirical study on the quality assessment of the VoIP service over wireless mobile networks;mining domain-dependent noun opinion words for sentiment analysis;personalized fitting with deviation adjustment based on support vector regression for recommendation;a quick and effective method for ranking authors in academic social network;navigation mechanism in blended context-aware ubiquitous learning environment;development of automotive multimedia system using visible light communications;research about virtualization of ARM-based mobile smart devices and secure resource synchronization of mobile peer-to-peer techniques.

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Monogenic Binary pattern (MBP): A Novel Feature Extraction and Representation Model for Face recognition

Monogenic Binary Pattern (MBP): A Novel Feature Extraction a...

引用

international conference on pattern recognition

作者： Meng Yang Lei Zhang Lin Zhang David Zhang Biometric Research Center Department of Computing Hong Kong Polytechnic University Hong Kong China

ISBN: (纸本)9781424475421

A novel feature extraction method, namely monogenic binary pattern (MBP), is proposed in this paper based on the theory of monogenic signal analysis, and the histogram of MBP (HMBP) is subsequently presented for robust face representation and recognition. MBP consists of two parts: one is monogenic magnitude encoded via uniform LBP, and the other is monogenic orientation encoded as quadrant-bit codes. The HMBP is established by concatenating the histograms of MBP of all sub-regions. Compared with the well-known and powerful Gabor filtering based LBP schemes, one clear advantage of HMBP is its lower time and space complexity because monogenic signal analysis needs fewer convolutions and generates more compact feature vectors. The experimental results on the AR and FERET face databases validate that the proposed MBP algorithm has better performance than or comparable performance with state-of-the-art local feature based methods but with significantly lower time and space complexity.

关键词： Face Histograms Face recognition Feature extraction Databases Complexity theory Filtering

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CUDA Implementation of Deformable pattern recognition and its Application to MNIST Handwritten Digit Database

CUDA Implementation of Deformable Pattern Recognition and it...

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international conference on pattern recognition

作者： Yoshiki Mizukami Katsumi Tadamura Jonathan Warrell Peng Li Simon Prince Graduate School of Science and Engineering Yamaguchi University Ube Japan Department of Computing Oxford Brookes University Oxford UK Department of Computer Science University College London London UK

ISBN: (纸本)9781424475421

In this study we propose a deformable pattern recognition method with CUDA implementation. In order to achieve the proper correspondence between foreground pixels of input and prototype images, a pair of distance maps are generated from input and prototype images, whose pixel values are given based on the distance to the nearest foreground pixel. Then a regularization technique computes the horizontal and vertical displacements based on these distance maps. The dissimilarity is measured based on the eight-directional derivative of input and prototype images in order to leverage characteristic information on the curvature of line segments that might be lost after the deformation. The prototype-parallel displacement computation on CUDA and the gradual prototype elimination technique are employed for reducing the computational time without sacrificing the accuracy. A simulation shows that the proposed method with the k-nearest neighbor classifier gives the error rate of 0.57% for the MNIST handwritten digit database.

关键词： Prototypes Pixel Error analysis Mathematical model Databases Character recognition

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pattern Identification using Rough Set Clustering for Spatio-Temporal Dataset

Pattern Identification using Rough Set Clustering for Spatio...

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international conference on Advances in computing, Communications and Informatics

作者： Christina Jayakumaran Komathy Karuppanan Department of Computer Science and Engineering Easwari Engineering College

ISBN: (纸本)9781467361262

Spatial temporal data mining is highly demanding because of the complexity of huge amount of data collected. Interpreting the spatial data is made easier by the process of visualizing quantitative spatial data leading to the discovery of interesting patterns. To understand the spatial structure of the data, better clustering algorithms are to be used. The purpose of this paper is to investigate the efforts of applying rough set theory onto spatial clustering. Rough set theory utilizes the spatial structure of the data resulting in better pattern identification. The results of our proposed model are compared with the hard clustering methods such as single linkage, ward's and density based clustering which proves that the rough set based soft clustering converges data points faster. Our investigation shows that the rough set based clustering helps in identifying clusters that are more cohesive compared with the hard partitioning clustering method. soft Clustering provides more information about the structure of the data than hard clustering.

关键词： Regionalization pattern identification Spatial distribution Air pollution Rough set Spatial and temporal data set K-means Hard clustering Cohesion Variance

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A fault diagnosis method for polymeric reaction process based on soft measuring hybrid model

A fault diagnosis method for polymeric reaction process base...

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international conference on Machine Learning and Cybernetics (ICMLC)

作者： Hui-Zhong Yang Su-Zhen Zhang Zhen-Lin Tao Bao-Tong Cui Research Center of Control Science and Control Engineering Southern Yangtze University Wuxi China Research Institute of Automation East China University of Science and Technology Shanghai China

This paper presented a fault diagnostic method for polymeric reaction process by means of the technique of adopted fuzzy pattern recognition. Based on soft measuring hybrid model, a threshold value principle and maximum membership degree principle are combined to diagnose faults. The fault diagnostic method is used for a typical polymeric reaction productive process - Polyacrylonitrile productive process, and it is proved that it can not only get accurate diagnosis results but also rectify the output of the hybrid model with the help of the information from morbid symptom set.

关键词： Fault diagnosis Polymers pattern recognition Fuzzy systems Fuzzy control Electrical equipment industry Nonlinear dynamical systems Fault detection Automatic control Control engineering

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