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4th International Conference on Advanced Design and Manufacturing Engineering, ADME 2014

作者： Hu, De Kun Zhang, L. Zhao, Wei Dong Yan, Tao Key Laboratory of Pattern Recognition and Intelligent Information Processing Institutions of Higher Education of Sichuan Province Chengdu University Chengdu China

ISBN: (纸本)9783038352570

In order to classify the objects in nature images, a model with color constancy and principle component analysis network (PCANet) is proposed. The new color constancy model imitates the functional properties of the HVS from the retina to the double-opponent cells in V1. PCANet can be designed and learned extremely, which comprises only the very basic data processing components: cascaded principal component analysis (PCA), binary hashing, and block-wise histograms. At last, a SVM is trained to classify the object in the image. The results of experiments demonstrate the potential of the model for object classification in wild color images. © (2014) Trans Tech Publications, Switzerland.

关键词： Object recognition

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recognition of facial expression via kernel PCA network 3

Recognition of facial expression via kernel PCA network

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3rd International Conference on Information Technology and Management Innovation, ICITMI 2014

作者： Hu, De Kun Ye, An Sheng Li, Li Zhang, Li Key Laboratory of Pattern Recognition and Intelligent Information Processing Institutions of Higher Education of Sichuan Province Chengdu University Chengdu China

ISBN: (纸本)9783038352396

In this work, a kernel principle component analysis network (KPCANet) is proposed for classification of the facial expression in unconstrained images, which comprises only the very basic data processing components: cascaded kernel principal component analysis (KPCA), binary hashing, and block-wise histograms. In the proposed model, KPCA is employed to learn multistage filter banks. It is followed by simple binary hashing and block histograms for indexing and pooling. For comparison and better understanding, We have tested these basic networks extensively on many benchmark visual datasets(such as the JAFFE [13] database, the CMU AMP face expression database, a part of the Extended Cohn-Kanade (CK+) database), The results demonstrate the potential of the KPCANet serving as a simple but highly competitive baseline for facial expression recognition. © 2014 Trans Tech Publications, Switzerland.

关键词： Database systems

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A Novel Ordinal Regression Method with Minimum Class Variance Support Vector Machine

A Novel Ordinal Regression Method with Minimum Class Varianc...

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2015 International Conference on Materials Engineering and Information Technology Applications(MEITA 2015)

作者： Jinrong Hu Xiaoming Wang Zengxi Huang School of Computer and Soft Engineering Xihua University Key Laboratory of Pattern Recognition and Intelligent Information Processing Chengdu University

ISBN: (纸本)9781510812055

In the paper, we propose a novel ordinal regression method called minimum class variance support vector ordinal regression(MCVSVOR). MCVSVOR is derived from minimum class variance support vector machine(MCVSVM) which is a variant of SVM, and so inherits the latter's characteristics such as taking the distribution of the categories into consideration and good generalization performance. Finally, the experimental results validate the effectiveness of MCVSVOR and indicate its superior generalization performance over SVOR.

关键词： Machine learning Ordinal regression Support vector machine Support vector ordinal regression

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Detection level of mango based on neural network and digital image

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Journal of Chemical and Pharmaceutical Research 2014年第2期6卷 129-132页

作者： Li, Xiaoling Yuan, Jimin School of Computer Science and Technology of Chengdu University China University Key Laboratory of Pattern Recognition and Intelligent Information Processing China Department Computer Engineering of Chengdu Aeronautic Vocational and Technical College China

In view of the draw backs of mango grade identification in China, which still relies on photoelectric sorting and manual separation, this paper presents a processing method on the basis of the technology of computer vision and digital image. Utilizing image processing technology, the researcher calculated the length of the long-short-axis, marked the location of it and calculated the 7 parameters, chroma, length, width and etc.,4 of which are chosen as the key characteristics of the BP input of network to build a network and identify the level of mango through analysis of the external characteristics of mango. The method is based on traditional characteristics detection, using boundary tracking algorithm and the length of the new long-short-axis detection algorithm. The result of experiment indicates that the calculating method and judging of the level of mango are precise and accurate, with an average recognition rate of 92%. Therefore, the method has a great practical value, which can be applied to other agricultural products classification.

关键词： Fruits

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pattern matching with flexible wildcard gaps

Pattern matching with flexible wildcard gaps

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5th International Symposium on IT in Medicine and Education, ITME 2013

作者： Junyan, Zhang Chenhui, Yang Information Science and Technology College Chengdu University Chengdu China Key Laboratory of Pattern Recognition and Intelligent Information Processing of Sichuan Chengdu University Chengdu China

ISBN: (纸本)9789400776173

pattern matching is a fundamental application in biomedicine and biological sequence analysis. A wildcard can match any one character in a sequence. Multiple wildcards form a gap. A flexible wildcard gap can match any characters with specific length which is specified by users. Therefore, the effective algorithm performing this kind of matching is in great need. In this paper, we design PMFG algorithm and achieve it by dividing a pattern into multiple sub-patterns with different length based on gap segmentation. After computing the starting positions and ending positions of each subpattern, the effective intervals and effective starting positions can be determined one by one. The number of the elements in the last effective position set equals to the number of the matching. A comparison experiments are done based on three DNA sequences. The results show that PMFG algorithm has better performance in the same fields. © Springer Science+Business Media Dordrecht 2014.

关键词： pattern matching

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Safety and health monitoring of bridge construction based on wireless sensor network

International Journal of Multimedia and Ubiquitous Engineeri...

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International Journal of Multimedia and Ubiquitous Engineering 2014年第3期9卷 257-268页

作者： Li, Xiaoling Yuan, Jimin School of Computer Science and Technology Chengdu University Chengdu 610106 China University Key Laboratory of Pattern Recognition and Intelligent information Processing Chengdu 610106 China The Department Computer Engineering Chengdu Aeronautic Vocational and Technical College Chengdu 610000 China

The existing safety and health monitoring methods for bridge construction are mainly manual monitoring and wired monitoring with many disadvantages, such as low efficiency, poor accuracy, great implementation difficulty, short bridge age, etc. To solve such problems, the paper provides a design scheme for the bridge construction safety and health monitoring System based on wireless sensor networks. In the system, various sensors are mainly used to collect data about the wind, temperature, traffic load, humidity, static position, static displacement and external load response, and then send to the host by route and gateway nodes. After data analysis and processing, the safety of the bridge is evaluated to help the personnel make correct bridge safety precautions. With such advantages as low power demand, wireless transmission of monitoring data, etc., the system is suitable for large range of promotion. © 2014 SERSC.

关键词： Data handling

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A Robust CPD Approach Based on Shape Context 33

A Robust CPD Approach Based on Shape Context

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第三十三届中国控制会议

作者： YANG Yawen ZHANG Peng Peng QIAO Yu YANG Jie WANG Sheng Zheng The Key Laboratory of Ministry of Education for System Control and Information Processing Institute of Image Processing and Pattern RecognitionShanghai Jiao Tong University Merchant Marine College Shanghai Maritime University

ISBN: (纸本)9781479947249

Point matching is an important component of image *** years,Coherent Point Drift(CPD) method becomes a very popular point matching *** treats point matching as a probability estimation problem and speeds up the process of matching a *** this method,one set of points are thought to be sampled from a Gaussian Mixture Model(GMM),which is centered by the other set of ***,CPD is sensitive to outliers and noises,especially when the noise ratio increased or the number of outliers gets much *** deal with this problem,we introduce shape context into the step of searching for matching points and then improve the form of prior probabilities of GMM in this *** main idea of our method is that if the most points in a data set are likely to be matched to a particular centroid,this Gaussian component should be have a more influence to ***,we set prior probability of GMM with the similarity between GMM components and the data *** the computation of similarity is based on shape *** experiments on 2D and 3D images show that when noise ratio is low,our method performs as well as CPD does,but as the ratio increased,our method is more robust and satisfactory than CPD.

关键词： CPD,Shape context,Image registration,Point matching

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Multi-view face detection based on multi-features adaboost collaborative learning algorithm

Multi-view face detection based on multi-features adaboost c...

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2014 International Conference on Applied Sciences, Engineering and Technology, ICASET 2014

作者： Huang, Rong Bing Zhang, Hong Shu, Chang Ming Key Laboratory of Pattern Recognition and Intelligent Information Processing of Sichuan Chengdu University Sichuan 610106 China School of Information Science and Technology Chengdu University Sichuan 610106 China

ISBN: (纸本)9783038351849

In view of the multi-view face detection problem under complex background, an improved face detection method based on multi-features boosting collaborative learning algorithm integrating local binary pattern (LBP) is presented. Firstly, facial skin color information is used to exclude most of the background regions. Then, Haar-like feature and LBP feature are extracted from facial candidate regions and inputted into a modified AdaBoost algorithm to obtain a strong classifier. Lastly, in order to improve the detection speed, pyramid classifier system structure is adopted to determine the face. The experimental results on CMU standard test set and life photos, the proposed method has achieved the rapid detection of multi-view face image. © (2014) Trans Tech Publications, Switzerland.

关键词： Face recognition

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High-level spatial modeling in convolutional neural network with application to pedestrian detection

High-level spatial modeling in convolutional neural network ...

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Canadian Conference on Electrical and Computer Engineering (CCECE)

作者： Feng Liu Yongzhen Huang Wankou Yang Changyin Sun School of Automation. Southeast University Nanjing China Key Lab of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China Key Lab of Child Development and Learning Science of Ministry of Education. Southeast University Nanjing China

ISBN: (纸本)9781479958306

Convolutional neural network (CNN) has achieved great success in many vision tasks. A key to this success is its ability to powerful automatically learns both high-level and low-level features. In general, low-level features have a small size of receptive fields and appear multiple times in different locations of objects, while high-level semantic features have a relatively large size of receptive fields and only appear once in a specific location of objects. However, traditional CNN treats these two kinds of features in the same manner, i.e., learning them by the convolution operation, which can be approximately considered as cumulating the probabilities that a feature appears in different locations. This strategy is reasonable for low-level features but not for high-level semantic ones, especially in the case of pedestrian detection, where a local feature can be shared by different locations but a semantic part, e.g., a head, only appears once for a human. To jointly model the spatial structure and appearance of high-level semantic features, we propose a new module to learn spatially weighted max pooling in CNN. The proposed method is evaluated on several pedestrian detection databases and the experimental results show that it achieves much better performance than traditional CNN.

关键词： Convolution Semantics Kernel Deformable models Computational modeling Feature extraction Training

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A new network traffic prediction algorithm based on discrete queue

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Journal of Computational Information Systems 2015年第12期11卷 4255-4261页

作者： Zhang, Hong Hu, Jun Shen, Yuncheng Key Laboratory of Pattern Recognition and Intelligent Information Processing Chengdu China College of Information Science and Technology Chengdu University Chengdu China College of Computer Science Sichuan University Chengdu China School of Traffic and Transportation Beijing Jiaotong University Beijing China Faculty of Computer Science Chengdu Normal University Chengdu China College of Information Science and Technology Zhaotong University Zhaotong China

In order to verify the network traffic decline because by node breakdown, this paper proposes a new type of prediction algorithm (Prediction algorithm based on Discrete-Queue for FARIMA model, PDF). At first, the mathematic formula for queuing situation and average queue length in steady state is derived with queuing theory in this algorithm based on discrete time, and the prediction method is established by FARIMA Model. Then, a simulation was conducted to research on the relationships between average queue length and service rate. The result shows that it has good adaptability, and the standard deviation between prediction traffic and original traffic is 10.18. ©, 2015, Binary Information Press. All right reserved.

关键词： Forecasting

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