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Memetic computation based on regulation between neural and immune systems: the framework and a case study

Science China(Information Sciences) 2010年第8期53卷 1519-1527页

作者： GONG MaoGuo , JIAO LiCheng, LIU Fang & YANG Jie key lab of Intelligent Perception and image Understanding of Ministry of Education of China, Institute of Intelligent Information processing, Xidian University, Xi’an 710071, China 1. Key Lab of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi’an 710071 China

Lamarckian learning has been introduced into evolutionary computation to enhance the ability of local search. The relevant research topic, memetic computation, has received significant amount of interest. In this study, a novel memetic computational framework is proposed by simulating the integrated regulation between neural and immune systems. The Lamarckian learning strategy of simulating the unidirectional regulation of neural system on immune system is designed. Consequently, an immune memetic algorithm based on the Lamarckian learning is proposed for numerical optimization. The proposed algorithm combines the advantages of immune algorithms and mathematical programming, and performs well in both global and local search. The simulation results based on ten low-dimensional and ten high-dimensional benchmark problems show that the immune memetic algorithm outperforms the basic genetic algorithm-based memetic algorithm in solving most of the test problems.

关键词： memetic computation artificial immune system Lamarckian learning genetic algorithm numerical optimization

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A novel improved method of pixel-domain Wyner-Ziv video coding

A novel improved method of pixel-domain Wyner-Ziv video codi...

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25th PCS: Picture Coding Symposium 2006, PCS2006

作者： Zongliang, Gan Lina, Qi Xiuchang, Zhu Province Key Lab. on Image Processing and Image Communication Communication and Information Engineering Institute Nanjing University of Posts and Telecommunications Nanjing 210003 China

ISBN: (纸本)300018726X

In distributed video coding (DVC), efficient compression is achieved by exploiting source statistics at the decoder only, which is radically different from conventional video coding. The pixel-domain Wyner-Ziv video coding is a kind of typical distributed video coding scheme, in which the encoder can be very simple and the complexity of the coder is transferred to the decoder. The performance of pixel-domain Wyner-Ziv video codec is greatly dependent on quality of side information and reconstruction arithmetic. In this paper we propose an improved method of pixel-domain Wyner-Ziv video coding based on side information estimate and decoding reconstruction at the decoder. The results of simulation tests show that better visual quality and average 1.5dB gain can be achieved by applying the proposed method.

关键词： image coding

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Learning Dual-Domain Calibration and Distance-Driven Correlation Filter:A Probabilistic Perspective for UAV Tracking

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Computers, Materials & Continua 2023年第12期77卷 3741-3764页

作者： Taiyu Yan Yuxin Cao Guoxia Xu Xiaoran Zhao Hu Zhu Lizhen Deng Jiangsu Province Key Lab on Image Processing and Image Communication Nanjing University of Posts and TelecommunicationsNanjingChina School of Computer Science Qufu Normal UniversityQufuChina National Engineering Research Center of Communication and Network Technology Nanjing University of Posts and TelecommunicationsNanjingChina

Unmanned Aerial Vehicle(UAV)tracking has been possible because of the growth of intelligent information technology in smart cities,making it simple to gather data at any time by dynamically monitoring events,people,the environment,and other aspects in the *** traditional filter creates a model to address the boundary effect and time filter degradation issues in UAV tracking *** these methods ignore the loss of data integrity terms since they are overly dependent on numerous explicit previous regularization *** light of the aforementioned issues,this work suggests a dual-domain Jensen-Shannon divergence correlation filter(DJSCF)model address the probability-based distance measuring issue in the event of filter *** two-domain weighting matrix and JS divergence constraint are combined to lessen the impact of sample imbalance and *** new tracking models that are based on the perspectives of the actual probability filter distribution and observation probability filter distribution are proposed to translate the statistical distance in the online tracking model into response *** model is roughly transformed into a linear equality constraint issue in the iterative solution,which is then solved by the alternate direction multiplier method(ADMM).The usefulness and superiority of the suggested strategy have been shown by a vast number of experimental findings.

关键词： Dual-domain weighting distance measure correlation filter ADMM

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Gait identification by sparse representation

Gait identification by sparse representation

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2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011, Jointly with the 2011 7th International Conference on Natural Computation, ICNC'11

作者： Gong, Minyan Xu, Yi Yang, Xiaokang Zhang, Wenjun Institute of Image Communication and Information Processing Shanghai China Shanghai Key Lab of Digital Media Processing and Transmissions Shanghai China

ISBN: (纸本)9781612841816

Gait recognition under variations of clothing and carrying condition is still a challenging task. In this paper, we present a gait identification method via sparse representation. We formulate the recognition problem as finding the coefficients of linear combination of the training samples plus an error term and discuss sparse signal representation theory that offers the solution to this problem. Based on the sparse representation computed by l1-minimization, we define a new distance metric to choose non-polluted area and propose a method for gait identification. Compared with the state-of-the-art methods on a large dataset, the proposed method achieves significant performance improvement in identification rates and it shows robustness to variations. © 2011 IEEE.

关键词： Pattern recognition

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A Regularized Super Resolution Algorithm for Generalized Gaussian Noise

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Journal of Donghua University(English Edition) 2010年第1期27卷 25-35页

作者：陈文方向忠刘立峰蒋伟丁大为乔艳涛 Institute of Image Communication and Information Processing Shanghai Jiaotong University Computer and Information Department Shanghai University of Electric Power Key Lab oratory of Intelligent Computing & Signal Processing Ministry of EducationAnhui University

In this paper,an iterative regularized super resolution (SR) algorithm considering non-Gaussian noise is *** on the assumption of a generalized Gaussian distribution for the contaminating noise,an lp norm is adopted to measure the data fidelity term in the cost *** the meantime,a regularization functional defined in terms of the desired high resolution (HR) image is employed,which allows for the simultaneous determination of its value and the partly reconstructed image at each iteration *** convergence is thoroughly *** results show the effectiveness of the proposed algorithm as well as its superiority to conventional SR methods.

关键词： super resolution generalized p-Gaussian distribution regularization parameter

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NiuTrans: An open source toolkit for phrase-based and syntax-based machine translation 50

NiuTrans: An open source toolkit for phrase-based and syntax...

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50th Annual Meeting of the Association for Computational Linguistics, ACL 2012

作者： Xiao, Tong Zhu, Jingbo Zhang, Hao Li, Qiang Natural Language Processing Lab Northeastern University Key Laboratory of Medical Image Computing Ministry of Education

ISBN: (纸本)9781937284275

We present a new open source toolkit for phrase-based and syntax-based machine translation. The toolkit supports several state-of-the-art models developed in statistical machine translation, including the phrase-based model, the hierachical phrase-based model, and various syntax-based models. The key innovation provided by the toolkit is that the decoder can work with various grammars and offers different choices of decoding algrithms, such as phrase-based decoding, decoding as parsing/tree-parsing and forest-based decoding. Moreover, several useful utilities were distributed with the toolkit, including a discriminative reordering model, a simple and fast language model, and an implementation of minimum error rate training for weight tuning. © 2012 Association for Computational Linguistics

关键词： Machine translation

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Track prediction algorithm based on GA-BPNN 3

Track prediction algorithm based on GA-BPNN

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3rd IEEE International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2021

作者： Jiao, Weidong Ma, Chong Tianjin Key Lab for Advanced Signal and Image Processing Civil Aviation University of China Tianjin China

ISBN: (纸本)9781665425186

A track prediction algorithm is proposed based on the Genetic Algorithm (GA) and Back Propagation neural network (BPNN), in which the GA is used to optimize the initial weights and thresholds of hidden layers of the network. Firstly, a 5-5-4 topology of the BPNN for track prediction is established according to the characteristics of track prediction. Its inputs are historical tracks, and the output just is the predicted track. Secondly, the weights and thresholds of the BPNN are regarded as genes of individual in GA to construct chromosomes, individuals, and populations. Then, the optimal solution of the GA is used as the weights and thresholds of the BPNN for network training to get a better output. In the experiment, the track data are derived from Automatic Dependent Surveillance-Broadcast, and experimental results show that the proposed algorithm can improve both the accuracy and time efficiency of the BPNN. In addition, we use the predicted track of the proposed method to detect flight conflict by constructing conflict scenarios. The detecting process and results are visualized in the Geographic Information System, and the correct results of detecting again show that the proposed method is reliable. © 2021 IEEE

关键词： Forecasting

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Estimation of visual ERP signals with nonextensive entropy

Estimation of visual ERP signals with nonextensive entropy

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ICBPE 2006 - 2006 International Conference on Biomedical and Pharmaceutical Engineering

作者： Minfen, Shen Bin, Li Hongrong, Tang Key Lab. of Digital Signal and Image Processing of Guangdong Province Shantou University Shantou China

ISBN: (纸本)8190426249

Nonextensive entropy, the Tsallis-like time-dependent entropy (TDE), is developed to study the event-related potential signals ( ERPs ) in a cue, "E"-orientation discrimination task. The statistical characteristics of the TDE for different signal distributions are studied. Results indicated that with the appearance of P2 and N2, a significant decrease of TDE was correlated with the responses to small size cue which supports the previous theoretic analysis. This method provides a novel quantitative measurement for ERPs actives and may be a useful tool in signals monitoring. © 2006 Research Publishing Services.

关键词： Entropy

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Wind Field Inversion and Reconstruction Based on ADS-B Data 3

Wind Field Inversion and Reconstruction Based on ADS-B Data

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3rd IEEE International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2021

作者： Xiaoyun, Shen Zixuan, Zhao Siyuan, Zhang Weidong, Jiao Chong, Ma Tianying, Wang Tianjin Key Lab for Advanced Signal and Image Processing Civil Aviation University of China Tianjin China

ISBN: (纸本)9781665425186

To accurately perceive sudden airflow changes during flight and avoid aviation safety risks caused by sudden weather at high altitudes, it is necessary to invert and reconstruct the wind field during flight. Based on the random sample consensus estimation, the improved Least Squares algorithm is used to fit the Automatic Dependent Surveillance-Broadcast (ADS-B) data. Firstly, the vertical wind profile is constructed by inverting the wind vectors at different altitude levels at the fixed airport location and compared with the meteorological data of the European Center for Medium-Range Weather Forecasts (ECMWF) to verify the feasibility and accuracy of the algorithm. Then, the wind field under the complete track of a specific flight is reconstructed to obtain the wind field distribution along the route. Finally, regional wind fields at different altitudes are reconstructed using multiaircraft data in a fixed range. The experimental results show that this method can better reflect the real complex wind field structure. © 2021 IEEE

关键词： Weather forecasting

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Static human behavior classification based on LLC features and GIST features 7

Static human behavior classification based on LLC features a...

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7th IEEE Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2017

作者： Ende, Wang Xukui, Hou Xuepeng, Li Shenyang Institute of Automation Chinese Academic of Sciences Key Lab of Image Understanding and Computer Vision Key Laboratory of Optical Electrical Image Processing Shenhe District Shenyang Liaoning China

ISBN: (纸本)9781538604892

This paper presents a method for recognizing human behavior in static images based on LLC and GIST features. The feature points in the image is densely located in sub-region of images and we extract SIFT feature from each sub-region. Then using the LLC method to encode the extracted dense SIFT features of each sub-region and each feature point descriptor is assigned to several nearest words, so that each descriptor can be expressed by the linear correlation coefficient of vocabulary. In order to increase the spatial information, we use the SPM model to divide the image into many blocks under different levels. We can get the pooled feature from each sub-region using the max pooling method. Then these pooled features from sub-region are concatenated and normalized as the final pooled features. In order to get GIST features, we divide the image into blocks and construct the Gabor filter group of 32 different scales and directions. Then each Gabor filter in the Gabor filter group does convolution operation with image blocks and we take the mean value of each blocks under each Gabor filter as the feature description. The features from each block under each Gabor filter are concatenated and normalized as the final GIST feature representation of the image. Then concatenating the final pooled features and the GIST features and take as the final feature representation. Finally, the intersection kernel function of SVM is used for classification. We performed experiments on several databases. By contrast, this algorithm has a good effect in accuracy and efficiency. © 2017 IEEE.

关键词： Gabor filters

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