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作者： Yanqiu Li Fuji Ren Min Hu Xiaohua Wang AnHui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information He Fei University of Technology

Fuzzy density is an important part of fuzzy integral, which is used to describe the reliability of classifiers in the process of fusion. Most of the fuzzy density assignment methods are based on the training priori knowledge of the classifier and ignore the difference of the testing samples themselves. To better describe the real-time reliability of the classifier in the fusion process, the dispersion of the classifier is calculated according to the decision information which outputted by the classifier. Then the divisibility of the classifier is obtained through the information entropy of the dispersion. Finally, the divisibility and the priori knowledge are combined to get the fuzzy density which can be dynamically adjusted. Experiments on JAFFE and CK databases show that, compared with traditional fuzzy integral methods, the proposed method can effectively improve the decision performance of fuzzy integral and reduce the interference of unreliable output information to decision. And it is an effective multi-classifier fusion method.

关键词： Fuzzy Density Facial expression recognition (FER) Fuzzy integral Divisibility

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Facial expression recognition based on DT-CWT and weighted inverse cloud model 15

Facial expression recognition based on DT-CWT and weighted i...

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15th IASTED International Conference on intelligent Systems and Control, ISC 2016

作者： Li, Yanqiu Ren, Fuji Hu, Min Anhui province Key Laboratory of Affective Computing and Advanced Intelligent Machines School of Computer and Information Hefei University of Technology Anhui230009 China

ISBN: (纸本)9780889869837

In order to describe the facial expression images in multi-scale better and weaken the influence of the edge information to recognition result, this paper proposes a method for describing the feature of the facial expression which uses the dual tree complex wavelet transform (DT-CWT) and Uniform Local Gradient Pattern (ULGP). To distinguish the contribution which feature information of different directions play in the recognition, and describe the randomness of the testing image, the cloud model is introduced in this paper. It uses the information entropy of features in different directions as the cloud droplet to obtain the membership degree of the testing image and get the adaptive weighting matrix of it. Moreover, at the recognition stage, combined with BP neural network, we obtain the posterior values which the testing image in different directions belong to different categories. Finally, we utilize the weighted fusion method of decision level to realize the recognition of the testing image. The experimental results on JAFFE database and CK database verify the validity of the feature extracting method in this paper, and the feasibility of using the cloud model to get adaptive weights. The system obtains higher recognition rate ultimately.

关键词： Wavelet transforms

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Correction to: Emotion recognition based on physiological signals using brain asymmetry index and echo state network

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Neural computing and Applications 2018年第10期32卷 6415-6415页

作者： Ren, Fuji Dong, Yindong Wang, Wei School of Computer and Information Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology Hefei China Graduate School of Advanced Technology and Science University of Tokushima Tokushima Japan

The authors quite agree that the AsI model is first developed by Panagiotis Petrantonakis from references [11] and [18] in their thesis.

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Detect the emotions of the public based on cascade neural network model 15

Detect the emotions of the public based on cascade neural ne...

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15th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2016

作者： Sun, Xiao Peng, Xiaoqi Ren, Fuji Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information Hefei University of Technology Hefei230009 China Faculty of Engineering University of Tokushima 2-1 Minami-Josanjima Tokushima770-8506 Japan

ISBN: (纸本)9781509008063

Along with the development of social network, more and more people know the world by reading news. The problem about what kind of emotion is inspired when people read news is very worthy of discussion. This paper will mix Deep Belief Networks (DBN) model and Support Vector Machine (SVM) to a hybrid neural network model by using the Contrast Divergence (CD) algorithm to estimate the weights when training a generating model, ensure that each layer of the Restricted Boltzmann Machine (RBM) mapping the features of the inputs to the best. At the same time, we cascade the last layer of DBN and a SVM classifier to adjust judging performance. And a set of tags will be attached to the top (Associative Memory), through a process of parameter tuning, learn the identifying weights to obtain a network for the task of text classification. The experimental results show that the hybrid neural network model works better than the traditional text categorization method based on simple characteristics (such as CHI), and it is more suitable for extracting text semantic characteristics. © 2016 IEEE.

关键词： Neural network models

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Detect the emotions of the public based on cascade neural network model

Detect the emotions of the public based on cascade neural ne...

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International Conference on Computer and Information Science (ACIS)

作者： Xiao Sun Xiaoqi Peng Fuji Ren Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology Hefei China Faculty of Engineering University of Tokushima Tokushima Japan

ISBN: (纸本)9781509008070

关键词： Visualization Training Support vector machines Classification algorithms Text categorization Artificial neural networks

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Differently implicational hierarchical inference algorithm under interval-valued fuzzy environment

Differently implicational hierarchical inference algorithm u...

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IEEE International Conference on Fuzzy Systems

作者： Yiming Tang Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information Hefei University of Technology Hefei 230009 P. R. China

ISBN: (纸本)9781467374293

Under interval-valued fuzzy environment, based on the differently implicational idea and hierarchical inference mechanism, the interval-valued universal triple I algorithm is put forward. To begin with, the interval-valued fuzzy implications and related residual pairs are researched. Furthermore, the interval-valued universal triple I principles are proposed, and the optimal solutions of the interval-valued universal triple I algorithm are achieved from the viewpoints of residual pairs together with the R-implications, and the corresponding hierarchical inference mode is established, meanwhile the reversible properties of the interval-valued universal triple I algorithm are proved. Finally, it is verified by examples that the interval-valued universal triple I algorithm performs better than the interval-valued triple I algorithm.

关键词： differently implicational idea hierarchical inference mechanism interval-valued universal

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Design and realization of 3D NOC multicast router base on multicast rotational routing arithmetic 5

Design and realization of 3D NOC multicast router base on mu...

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5th International Conference on computing Communication and Networking Technologies, ICCCNT 2014

作者： Wang, Wei Li, Runfeng Fang, Fang Chen, Tian Ren, Fuji Liu, Jun Wu, Xi Hefei University of Technology Hefei230009 China Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine 230009 China

ISBN: (纸本)9781479926961

Traditional 3D NoC router may encounter the situations of congestion and hot spot. And it also doesn't have the function of multicast. In this paper, we present a new routing arithmetic called Multicast Rotational Routing Arithmetic (MRRA). It can handle several destination addresses at the same time, recombine packets, sent the same data to the different destination nodes, and avoid the congestion. The proposed algorithm is implemented by the new multicast 3D NoC router which is also proposed in this paper. The 3D NoC router is designed in Verilog HDL, simulated by Modelsim, synthesized and prototyped by Synplify and FPGA respectively. The experiment results show that the multicast router of MRRA can achieve a very good performance in terms of throughput and delay. The increased area utilization also can be tolerated. © 2014 IEEE.

关键词： Network-on-chip

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Semantic polarity detection of Chinese multiword expression in microblogging based on discriminative latent model

Semantic polarity detection of Chinese multiword expression ...

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作者： Sun, Xiao Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information Hefei University of Technology Hefei230009 China

Extracting semantic polarity of Chinese Multiword Expression, especially some newly generated Multiword Expression from internet(such as weibo or microblog), is an important task for sentiment analysis of web texts or other real word text as some Multiword Expressions can express more integrative sentiments than words units. This paper proposes a method that contains a novel latent discriminative algorithm, which attempts to attack this problem by integrating discriminative model and latent value model. Although Chinese Multiword Expressions consist of multiple words, the semantic polarity of the Multiword Expression is not just simple integration of polarities of the component words, as some words can invert the affective polarity so the Multiword Expressions can have totally opposite semantic polarity, such as ironic texts. In order to capture the property of such Multiword Expressions, hidden semi-CRF which includes a latent valuable layer, which can be used to address dual-sequence labeling tasks synchronously, is adopted. The method is tested experimentally by adopting a manually labeled set of positive and negative Multiword Expressions from microblog or other internet resources, and the experiments have shown very promising results, which is comparable to the best value ever reported. © 2014-IOS Press and the authors. All rights reserved.

关键词： Sentiment analysis

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Chinese microblogging emotion classification based on support vector machine 5

Chinese microblogging emotion classification based on suppor...

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5th International Conference on computing Communication and Networking Technologies, ICCCNT 2014

作者： Sun, Xiao Li, Chengcheng Ye, Jiaqi Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information Hefei University of Technology Hefei230009 China

ISBN: (纸本)9781479926961

Through the analysis and study of the emotional characteristics in Chinese micro-blog, this paper proposed a multidimensional sentiment classification method based micro-blog emotion classification, emoticon in micro-blog is adopted to train the support vector machine and divide micro-blog into seven types of emotions: happiness, fondness, sorrow, anger, fear, detestation and surprise. We used micro-blog emoticon to initial screen large-scale unmarked data, and automatically labeled them into seven types, then used this emotional corpus as training set to train the emotion classifier to classify micro-blog data into multiple emotion categories. The experimental results show that precision of unigram model for each type can reach 63.7%. Meanwhile, different feature selection methods for support vector machines and Naive Bayes classifier experiment have been adopted in the experiment, the precision and recall has reached more than 71%. © 2014 IEEE.

关键词： Support vector machines

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Gene-disease association extraction by text mining and network analysis 5

Gene-disease association extraction by text mining and netwo...

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5th International Workshop on Health Text Mining and Information Analysis, Louhi 2014 at the 14th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2014

作者： Quan, Changqin Ren, Fuji AnHui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information HeFei University of Technology China Faculty of Engineering University of Tokushima Japan

ISBN: (纸本)9781937284909

Biomedical relations play an important role in biological processes. In this work, we combine information filtering, grammar parsing and network analysis for gene-disease association extraction. The proposed method first extracts sentences potentially containing information about gene-diseases interactions based on maximum entropy classifier with topic features. And then Probabilistic Context-Free Grammars is applied for gene-disease association extraction. The network of genes and the disease is constituted by the extracted interactions, network centrality metrics are used for calculating the importance of each gene. We used breast cancer as testing disease for system evaluation. The 31 top ranked genes and diseases by the weighted degree, betweenness, and closeness centralities have been checked relevance with breast cancer through NCBI database. The evaluation showed 83.9% accuracy for the testing genes and diseases, 74.2% accuracy for the testing genes. © 2014 Association for Computational Linguistics

关键词： Genes

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