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检索条件"机构=Affective Computing and Advanced Intelligent Machines Key Laboratory"

共 109 条记录，以下是61-70 订阅

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FRUIT RECOGNITION BASED ON MULTI-FEATURE AND MULTI-DECISION

FRUIT RECOGNITION BASED ON MULTI-FEATURE AND MULTI-DECISION

引用

2014 IEEE 3rd International Conference on Cloud computing and Intelligence Systems

作者： Xiaohua Wang Wei Huang Chao Jin Min Hu Fuji Ren Affective Computing and Advanced Intelligent Machines Anhui Key Laboratory School of Computer and Information Hefei University of Technology

In order to overcome the existing fruit recognition method only for single feature recognition which leads the problem of lower recognition rate,this paper proposes a recognition method based on multi-feature and ***,we preprocess the fruit image which is to be classified,separateing foreground and background,and then we divide the target ***,in order to take full advantage of multi-independence and complementarity between features,we extract the color,shape and texture of fruits image and put these features into the BP neural network to ***,the results of different features are put into the decision-making mechanisms to obtain a final recognition *** experiment results on object library and self-built library that is built by ourselves show that the method has good identification ability to fruit recognition and achieve the goal to identify different fruit.

关键词： fruit features BP neural network multi-feature multi-decision

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Real Time Early-stage Influenza Detection with Emotion Factors from Sina Microblog 5

Real Time Early-stage Influenza Detection with Emotion Facto...

引用

5th Workshop on South and Southeast Asian NLP, WSSANLP 2014

作者： Sun, Xiao Ye, Jiaqi Ren, Fuji School of Computer and Information Hefei University of Technology Anhui Hefei China Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine China Faculty of Engineering University of Tokushima Tokushima Japan

ISBN: (纸本)9781873769416

Influenza is an acute respiratory illness that occurs every year. Detection of Influenza in its earliest stage would reduce the spread of the illness. Sina microblog is a popular microblogging service, provides perfect sources for flu detection due to its real-time nature and large number of users. In this paper we investigate the real-time flu detection problem and describe a Flu model with emotion factors and sematic information (em-flu model). Experimental results show the robustness and effectiveness of our method and we are hopeful that it would help health organizations in identifying flu outbreak and take timely actions to control. © 2014 Proceedings of the Conference - 5th Workshop on South and Southeast Asian NLP, WSSANLP 2014 - co-located with the 25th International Conference on Computational Linguistics, COLING 2014. All rights reserved.

关键词： Diseases

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Expression image preprocessing based on wavelet transform

Expression image preprocessing based on wavelet transform

引用

2014 IEEE International Conference on Robotics and Biomimetics, IEEE ROBIO 2014

作者： Quan, Changqin Xu, Xiaoming Ren, Fuji Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information Hefei University of Technology Hefei230009 China University of Tokushima Shinkura-cho Tokushima770-8501 Japan

ISBN: (纸本)9781479973965

In this paper, we present a new image preprocessing method which is based on Wavelet Transform. Before we extract expression texture information, Wavelet transform will be applied to remove partial high frequency information. And then Gabor Transform will be used to extract expression information. At last we chose the Support Vector Machine to classify facial expressions. Experiments on the Japanese Female Facial Expression (JAFFE) Database illustrate that the Wavelet Transform and Gabor features are effective for facial expression discrimination. Additionally, the experiment results validate the feasibility of this method. © 2014 IEEE.

关键词： Wavelet transforms

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Fruit recognition based on multi-feature and multi-decision

Fruit recognition based on multi-feature and multi-decision

引用

IEEE International Conference on Cloud computing and Intelligence Systems (CCIS)

作者： Xiaohua Wang Wei Huang Chao Jin Min Hu Fuji Ren School of Computer and Information Hefei University of Technology Anhui China Affective Computing and Advanced Intelligent Machines Anhui Key Laboratory The University of Tokushima Japan

ISBN: (纸本)9781467369541

In order to overcome the existing fruit recognition method only for single feature recognition which leads the problem of lower recognition rate, this paper proposes a recognition method based on multi-feature and multi-decision. Firstly, we preprocess the fruit image which is to be classified, separating foreground and background, and then we divide the target area. Secondly, in order to take full advantage of multi-independence and complementarity between features, we extract the color, shape and texture of fruits image and put these features into the BP neural network to classify. Finally, the results of different features are put into the decision-making mechanisms to obtain a final recognition result. The experiment results on object library and self-built library that is built by ourselves show that the method has good identification ability to fruit recognition and achieve the goal to identify different fruit.

关键词： Machine vision Image recognition Image segmentation Image color analysis Shape Image resolution

来源：评论

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FACE RECOGNITION BASED ON ADAPTIVE WEIGHTING AND FUZZY FUSION WITH SINGLE TRAINING SAMPLE

FACE RECOGNITION BASED ON ADAPTIVE WEIGHTING AND FUZZY FUSIO...

引用

2014 IEEE 3rd International Conference on Cloud computing and Intelligence Systems

作者： Xiaohua Wang Chao Jin Wei Liu Min Hu Fuji Ren Affective Computing and Advanced Intelligent Machines Anhui Key Laboratory School of Computer and Information Hefei University of Technology The University of Tokushima 770-8506Japan

In order to solve the robustness issues for single training sample face recognition under occlusion conditions,this paper presents a recognition method based on adaptive weighting and fuzzy *** our method,the information entropy expansion mode is introduced in sub-mode method and via adaptively assigning the weights corresponding to each sub-model can reduce the impact of occluded *** addition,through summing the similar blocks in face images can make up for the defect of the sub-model which ignores the integrity of ***,the method based on fuzzy comprehensive evaluation is utilized for decision-level fusion to the outputs by these two ways of *** results on AR face database show that this method has state-of-the-art classification accuracy and also robustness to occlusion.

关键词： Face recognition Single training sample Adaptive weighting Fuzzy comprehensive evaluation Sub-model

来源：评论

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Adaptive facial expression recognition method based on MBP and HMOG feature

Adaptive facial expression recognition method based on MBP a...

引用

IEEE International Conference on Cloud computing and Intelligence Systems (CCIS)

作者： Min Hu Xiaoyin Huang Xiaohua Wang Kun Li Fuji Ren Liangfeng Xu School of Computer and Information Hefei University of Technology Anhui China Affective Computing and Advanced Intelligent Machines Anhui Key Laboratory The University of Tokushima Japan

ISBN: (纸本)9781467369541

Because of the limitation of Monogenic waves' extraction from expression texture, this thesis proposes an adaptive facial expression feature fusion method based on MBP (monogenic binary pattern) and Histogram of HMOG (monogenic orientated gradients). To begin with our method, we get information of orientation, phase and magnitude component from filtered image by monogenic waves, besides, extract and fuse texture information from orientation and magnitude component to recognize facial expression. However single texture feature have some inadequacies for facial expression recognition. First of all, this paper describes a new kind of HMOG feature inspired by thoughts of HOG (histogram of oriented gradients) to indicate shape information of facial image. Secondly, acquiring best adaptive weights of expression block through information entropy. Finally, we classify the expression image using Nearest Neighbor to get the final result of effect of proposed method. In order to verify the efficiency of the methods above, we do a large number of experiments and it turns out our methods have great ability to explain expression feature.

关键词： Feature extraction Face Entropy Information filters Databases Computers

来源：评论

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Age estimation and gender classification of facial images based on Local Directional Pattern

Age estimation and gender classification of facial images ba...

引用

IEEE International Conference on Cloud computing and Intelligence Systems (CCIS)

作者： Min Hu Yaona Zheng Fuji Ren He Jiang School of Computer and Information Hefei University of Technology Anhui China Affective Computing and Advanced Intelligent Machines Anhui Key Laboratory The University of Tokushima Japan

ISBN: (纸本)9781467369541

In order to improve shortage of Local Binary Pattern (LBP) algorithm in the field of facial feature extraction, this paper uses Local Directional Pattern (LDP) algorithm to extract the facial features about age estimation and gender classification. Because gradient information is more stable than gray information, LDP algorithm is not affected easily by noise. After preprocessing images, we use block strategy to represent facial features more fully. And then, we extract features of each block with LDP algorithm, storing the LDP histogram. Finally, we obtain age and gender identification results by Support Vector Machine (SVM). Experimental results on FG-NET face database show that this method has a good effect on age estimation and gender classification.

关键词： Face Feature extraction Estimation Interference Principal component analysis

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Face recognition based on adaptive weighting and fuzzy fusion with single training sample

Face recognition based on adaptive weighting and fuzzy fusio...

引用

IEEE International Conference on Cloud computing and Intelligence Systems (CCIS)

作者： Xiaohua Wang Chao Jin Wei Liu Min Hu Fuji Ren School of Computer and Information Hefei University of Technology Anhui China Affective Computing and Advanced Intelligent Machines Anhui Key Laboratory The University of Tokushima Japan

In order to solve the robustness issues for single training sample face recognition under occlusion conditions, this paper presents a recognition method based on adaptive weighting and fuzzy fusion. In our method, the information entropy expansion mode is introduced in sub-mode method and via adaptively assigning the weights corresponding to each sub-model can reduce the impact of occluded region. In addition, through summing the similar blocks in face images can make up for the defect of the sub-model which ignores the integrity of face. Finally, the method based on fuzzy comprehensive evaluation is utilized for decision-level fusion to the outputs by these two ways of classification. Experimental results on AR face database show that this method has state-of-the-art classification accuracy and also robustness to occlusion.

关键词： Robustness Testing

来源：评论

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AGE ESTIMATION AND GENDER CLASSIFICATION OF FACIAL IMAGES BASED ON LOCAL DIRECTIONAL PATTERN

AGE ESTIMATION AND GENDER CLASSIFICATION OF FACIAL IMAGES BA...

引用

2014 IEEE 3rd International Conference on Cloud computing and Intelligence Systems

作者： Min Hu Yaona Zheng Fuji Ren He Jiang Affective Computing and Advanced Intelligent Machines Anhui Key Laboratory School of Computer and Information Hefei University of Technology The University of Tokushima 770-8506Japan

In order to improve shortage of Lxical Binary Pattern(LBP) algorithm in the field of facial feature extraction,this paper uses Lxical Directional Pattern(LDP) algorithm to extract the facial features about age estimation and gender *** gradient information is more stable than gray information,LDP algorithm is not affected easily by *** preprocessing images,we use block strategy to represent facial features more *** then,we extract features of each block with LDP algorithm,storing the LDP histogram Finally,we obtain age and gender identification results by Support Vector Machine(SVM).Experimental results on FG-NET face database show that this method has a good effect on age estimation and gender classification.

关键词： feature extraction,LDP,age estimation,gender classification

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ADAPTIVE FACIAL EXPRESSION RECOGNITION METHOD BASED ON MBP AND HMOG FEATURE

ADAPTIVE FACIAL EXPRESSION RECOGNITION METHOD BASED ON MBP A...

引用

2014 IEEE 3rd International Conference on Cloud computing and Intelligence Systems

作者： Min Hu Xiaoyin Huang Xiaohua Wang Kun Li Fuji Ren Liangfeng Xu Affective Computing and Advanced Intelligent Machines Anhui Key Laboratory School of Computer and Information Hefei University of Technology The University of Tokushima 770-8506Japan

Because of the limitation of Monogenic waves’ extraction from expression texture,this thesis proposes an adaptive facial expression feature fusion method based on MBP（monogenic binary pattern） and Histogram of HMOG（monogenic orientated gradients）.To begin with our method,we get information of orientation,phase and magnitude component from filtered image by monogenic waves,besides,extract and fuse texture information from orientation and magnitude component to recognize facial *** single texture feature have some inadequacies for facial expression *** of all,this paper describes a new kind of HMOG feature inspired by thoughts of HOG（histogram of oriented gradients） to indicate shape information of facial ***,acquiring best adaptive weights of expression block through information ***,we classify the expression image using Nearest Neighbor to get the final result of effect of proposed *** order to verify the efficiency of the methods above,we do a large number of experiments and it turns out our methods have great ability to explain expression feature.

关键词： Monogenic signal Histogram of Monogenic Oriented Gradients Adaptive weights by information entropy Nearest Neighbor

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