检索结果-内蒙古大学图书馆

2017 International Conference on Advances in Image Processing, ICAIP 2017

作者： Hu, Min Teng, Wendi Zheng, Yaona Zhang, Keke AnHui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information HeFei University of Technology NO.193 Tunxi road Hefei230009 China

ISBN: (纸本)9781450352956

Feature extraction and estimation method are two key components of age estimation. This paper proposes a novel age estimation method based on Multi Levels Gaussian Mixture Model (MLGMM) and double layers estimation model. In the feature extraction phase, ML-GMM is used to construct different GMMs for different level features, which can well reflect the global and local age feature of facial images. In the estimation phase, double layers estimation model based on SVM-KNN is proposed. The first layer roughly divides age groups by using SVM. The second layer adopts KNN theory to find K images of consecutive age which have minimum sum of distance with the testing sample. The specific age is obtained by weighting these K age values. This paper performs a lot of experiments on mixed age database of FG-NET and MORPH-II databases. The mean absolute errors of age estimation are 3.22 years. Experimental results show that the proposed method is more effective than other methods of state-of-the-art for age estimation of facial images. It can extract more rich and complete age feature, improve the generalization ability of age estimation and reduce the mean absolute errors. © 2017 Association for computing Machinery.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

A fusion decision method based on the dynamic fuzzy density assignment 17

A fusion decision method based on the dynamic fuzzy density ...

引用

2017 International Conference on Advances in Image Processing, ICAIP 2017

作者： Li, Yanqiu Ren, Fuji Hu, Min Wang, Xiaohua AnHui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information HeFei University of Technology NO.193 Tunxi road Hefei230009 China

ISBN: (纸本)9781450352956

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. © 2017 Association for computing Machinery.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

Method of Age Estimation Based on ML-GMM Feature and Double Layers Estimation Model

Method of Age Estimation Based on ML-GMM Feature and Double ...

引用

作者： Min Hu Wendi Teng Yaona Zheng Keke Zhang AnHui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information He Fei University of Technology

Feature extraction and estimation method are two key components of age estimation. This paper proposes a novel age estimation method based on Multi Levels Gaussian Mixture Model(MLGMM) and double layers estimation model. In the feature extraction phase, ML-GMM is used to construct different GMMs for different level features, which can well reflect the global and local age feature of facial images. In the estimation phase, double layers estimation model based on SVM-KNN is proposed. The first layer roughly divides age groups by using SVM. The second layer adopts KNN theory to find K images of consecutive age which have minimum sum of distance with the testing sample. The specific age is obtained by weighting these K age values. This paper performs a lot of experiments on mixed age database of FG-NET and MORPH-II databases. The mean absolute errors of age estimation are 3.22 years. Experimental results show that the proposed method is more effective than other methods of state-of-the-art for age estimation of facial images. It can extract more rich and complete age feature, improve the generalization ability of age estimation and reduce the mean absolute errors.

关键词： Multi Levels Gaussian Mixture Model SVM KNN Age Estimation

来源：评论

学校读者我要写书评

暂无评论

A Fusion Decision Method Based on the Dynamic Fuzzy Density Assignment

A Fusion Decision Method Based on the Dynamic Fuzzy Density ...

引用

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

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

来源：评论

学校读者我要写书评

暂无评论

Extension of the non-parametric cluster-based time-frequency statistics to the full time windows and to single condition tests

arXiv

引用

arXiv 2018年

作者： Beste, Christian Kaping, Daniel Tzvetanov, Tzvetomir Cognitive Neurophysiology Department of Child and Adolescent Psychiatry Faculty of Medicine TU Dresden Germany National Institute of Mental Health Klecany Czech Republic CAS Key Laboratory of Brain Function and Disease School of Life Sciences University of Science and Technology of China Hefei Anhui230027 China Anhui Key Laboratory for Affective Computing and Advanced Intelligent Machines School of Computer and Information Hefei University of Technology Hefei Anhui230009 China

Oscillatory processes are central for the understanding of the neural bases of cognition and behaviour. To analyse these processes, time-frequency (TF) decomposition methods are applied and non-parametric cluster-based statistical procedure are used for comparing two or more conditions. While this combination is a powerful method, it has two drawbacks. One the unreliable estimation of signals outside the cone-of-influence and the second relates to the length of the time frequency window used for the analysis. Both impose constrains on the non-parametric statistical procedure for inferring an effect in the TF *** we extend the method to reliably infer oscillatory differences within the full TF mapand to test single *** show that it can be applied in small time windowsirrespective of the cone-of-influence and we further develop its application to single-condition case for testing the hypothesis of the presence or not of time-varying *** present tests of this new method on real EEG and behavioural data and show thatits sensitivity to single-condition testsis at least as good as classic Fourier *** inference in the full TF map is available and efficient in detecting differences between conditions as well as the presence of time-varying signal in single condition. Copyright © 2018, The Authors. All rights reserved.

关键词： Fourier analysis

来源：评论

学校读者我要写书评

暂无评论

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

引用

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.

关键词：

来源：评论

学校读者我要写书评

暂无评论

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

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

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

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

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

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

Perovskite Solar Cells: Unique Seamlessly Bonded CNT@Graphene Hybrid Nanostructure Introduced in an Interlayer for Efficient and Stable Perovskite Solar Cells (Adv. Funct. Mater. 32/2018)

引用

advanced Functional Materials 2018年第32期28卷

作者： Xuanhua Li Tengteng Tong Qinjiang Wu Shaohui Guo Qiang Song Jian Han Zhixiang Huang State Key Laboratory of Solidification Processing Research and Development Institute of Northwestern Polytechnical University In Shenzhen Center for Nano Energy Materials School of Materials Science and Engineering Northwestern Polytechnical University and Shaanxi Joint Lab of Graphene (NPU) Xi'an 710072 China Northwestern Polytechnical University‐Queen Mary University of London (NPU‐QMUL) Joint Research Institute of Advanced Materials and Structures (JRI‐AMAS) Xi'an 710072 China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University No. 3 Feixi Road Hefei Anhui Province 230039 P. R. China

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：