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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Ye Tian Shichen Peng Tobias Rodemann Xingyi Zhang Yaochu Jin Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Institutes of Physical Science and Information Technology Anhui University Hefei China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei China Honda Research Institute Europe Offenbach/Main Germany Department of Computer Science University of Surrey Guildford Surrey United Kingdom

ISBN: (数字)9781728124858

ISBN: (纸本)9781728124865

In the last two decades, many evolutionary algorithms have shown promising performance in solving a variety of multi-objective optimization problems (MOPs). Since there does not exist an evolutionary algorithm having the best performance on all the MOPs, it is unreasonable to use a single evolutionary algorithm to tackle all the MOPs. Since many real-world MOPs are computationally expensive, selecting the best evolutionary algorithm from multiple candidates via empirical comparisons is also impractical. To address the above issues, this paper proposes an automated algorithm selection method for choosing the most suitable evolutionary algorithm for a given MOP. The proposed method establishes a predictor based on the performance of a set of candidate evolutionary algorithms on multiple benchmark MOPs, where the inputs of the predictor are the explicit and implicit features of an MOP, and the output is the index of the evolutionary algorithm having the best performance on the MOP. Experimental results indicate that the evolutionary algorithm suggested by the proposed method is highly competitive among all the candidate evolutionary algorithms, demonstrating the practical value of the proposed method for engineers to select an evolutionary algorithm for their applications.

关键词： Evolutionary computation Benchmark testing Feature extraction Optimization Prediction algorithms Convergence Linear programming

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On efficient and robust metrics for RANSAC hypotheses and 3D rigid registration

arXiv

引用

arXiv 2020年

作者： Yang, Jiaqi Huang, Zhiqiang Quan, Siwen Zhang, Qian Zhang, Yanning Cao, Zhiguo National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science Northwestern Polytechnical University China School of Software Northwestern Polytechnical University Xi’an710129 China School of Electronic and Control Engineering Chang’an University Xi’an710064 China School of Resources and Environment Hubei University Wuhan430062 China National Key Laboratory of Science and Technology on Multi-spectral Information Processing School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

This paper focuses on developing efficient and robust evaluation metrics for RANSAC hypotheses to achieve accurate 3D rigid registration. Estimating six-degree-of-freedom (6-DoF) pose from feature correspondences remains a popular approach to 3D rigid registration, where random sample consensus (RANSAC) is a de-facto choice to this problem. However, existing metrics for RANSAC hypotheses are either time-consuming or sensitive to common nuisances, parameter variations, and different application scenarios, resulting in performance deterioration in overall registration accuracy and speed. We alleviate this problem by first analyzing the contributions of inliers and outliers, and then proposing several efficient and robust metrics with different designing motivations for RANSAC hypotheses. Comparative experiments on four standard datasets with different nuisances and application scenarios verify that the proposed metrics can significantly improve the registration performance and are more robust than several state-of-the-art competitors, making them good gifts to practical applications. This work also draws an interesting conclusion, i.e., not all inliers are equal while all outliers should be equal, which may shed new light on this research problem. Copyright © 2020, The Authors. All rights reserved.

关键词： Deterioration

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DeepACE: Automated chromosome enumeration in metaphase cell images using deep convolutional neural networks

arXiv

引用

arXiv 2019年

作者： Xiao, Li Luo, Chunlong Luo, Yufan Yu, Tianqi Tian, Chan Qiao, Jie Zhao, Yi Key Laboratory of Intelligent Information Processing Advanced Computer Research Center Institute of Computing Technology Chinese Academy of Sciences Beijing China Peking University Third Hospital Beijing China Beijing China

Chromosome enumeration is an important but tedious procedure in karyotyping analysis. In this paper, to automate the enumeration process, we developed a chromosome enumeration framework, DeepACE, based on the region based object detection scheme. Firstly, the ability of region proposal network is enhanced by a newly proposed Hard Negative Anchors Sampling to extract unapparent but important information about highly confusing partial chromosomes. Next, to alleviate serious occlusion problems, we novelly introduced a weakly-supervised mechanism by adding a Template Module into classification branch to heuristically separate overlapped chromosomes. The template features are further incorporated into the NMS procedure to further improve the detection of overlapping chromosomes. In the newly collected clinical dataset, the proposed method outperform all the previous method, yielding an mAP with respect to chromosomes as 99.45, and the error rate is about 2.4%. Copyright © 2019, The Authors. All rights reserved.

关键词： Chromosomes

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A embedding model for text classification

引用

Expert Systems 2019年第6期36卷 e12460-e12460页

作者： Liu, Wenfeng Liu, Peiyu Yang, Yuzhen Yi, Jing Zhu, Zhenfang School of Information Science and Engineering Shandong Normal University Jinan China School of Computer Heze University Heze China Shandong Normal University Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Jinan China School of Computer Science and Technology Shandong Jianzhu University Jinan China School of Information Science and Electrical Engineering Shandong Jiaotong University Jinan China

Existing word embeddings learning algorithms only employ the contexts of words, but different text documents use words and their relevant parts of speech very differently. Based on the preceding assumption, in order to obtain appropriate word embeddings and further improve the effect of text classification, this paper studies in depth a representation of words combined with their parts of speech. First, using the parts of speech and context of words, a more expressive word embeddings can be obtained. Further, to improve the efficiency of look-up tables, we construct a two-dimensional table that is in the format to represent words in text documents. Finally, the two-dimensional table and a Bayesian theorem are used for text classification. Experimental results show that our model has achieved more desirable results on standard data sets. And it has more preferable versatility and portability than alternative models. © 2019 John Wiley & Sons, Ltd

关键词： Embeddings

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Research on Network Intrusion Detection Based on Support Vector Machine Optimized with Grasshopper Optimization Algorithm

Research on Network Intrusion Detection Based on Support Vec...

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IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems

作者： Zhiwei Ye Yiheng Sun Shuang Sun Sikai Zhan Han Yu Quanfeng Yao Key Laboratory of Intelligent Computing and Information Processing Fujian Province University School of computer Science Hubei university of Technology Wuhan China Wuhan FiberHome Technical Services Co. Ltd.

As one of the most important parts of network security, more significance is attached to intrusion detection system (IDS). Numerous techniques including support vector machine (SVM) have been applied to the intrusion detection. However, many methods are utilized to improve the original SVM whose performance is markedly depended on its kernel parameters. Evolutionary algorithms such as genetic algorithm (GA) and particle swarm algorithm (PSO) are also employed to search better kernel parameters while the traditional optimization methods are vulnerable to fall into local minima with slow speed of convergence. In order to improve the precision of SVM in intrusion detection, the support vector machine based on grasshopper optimization algorithm (GOA-SVM) is proposed in the paper. To verify the practicality of the proposed method, several contrast experiments have been carried out using tool of Matlab. The experimental results finally demonstrates the superior performance of the proposed method on intrusion detection.

关键词： Support vector machines Optimization Intrusion detection Kernel Genetic algorithms Particle swarm optimization Artificial neural networks

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Evidence of Minijet Emission in a Large Emission Zone from a Magnetically Dominated Gamma-Ray Burst Jet

引用

Astrophysical Journal 2025年第2期985卷 239-239页

作者： Yi, S.-X. Wang, C.-W. Shao, X. Moradi, R. Gao, H. Zhang, B. Xiong, S.-L. Zhang, S.-N. Tan, W.-J. Liu, J.-C. Xue, W.-C. Zhang, Y.-Q. Zheng, C. Wang, Y. Zhang, P. An, Z.-H. Cai, C. Feng, P.-Y. Gong, K. Guo, D.-Y. Huang, Y. Li, B. Li, X.-B. Li, X.-Q. Liu, X.-J. Liu, Y.-Q. Ma, X. Peng, W.-X. Qiao, R. Song, L.-M. Wang, J. Wang, P. Wang, Y. Wen, X.-Y. Xiao, S. Xu, Y.-B. Yang, S. Yi, Q.-B. Zhang, D.-L. Zhang, F. Zhang, H.-M. Zhang, J.-P. Zhang, Z. Zhao, X.-Y. Zhao, Y. Zheng, S.-J. Key Laboratory of Particle Astrophysics Institute of High Energy Physics Chinese Academy of Sciences Beijing 100049 China University of Chinese Academy of Sciences Chinese Academy of Sciences Beijing 100049 China Department of Astronomy Beijing Normal University Beijing 100875 China Nevada Center for Astrophysics University of Nevada Las Vegas 89154 NV United States Department of Physics and Astronomy University of Nevada Las Vegas 89154 NV United States ICRANet Piazza della Repubblica 10 Pescara I-65122 Italy ICRA Dipartamento di Fisica Sapienza Università di Roma Piazzale Aldo Moro 5 Rome I-00185 Italy INAF Osservatorio Astronomico d’Abruzzo Via M. Maggini snc Teramo I-64100 Italy College of Electronic and Information Engineering Tongji University Shanghai 201804 China College of Physics Hebei Key Laboratory of Photophysics Research and Application Hebei Normal University Hebei Shijiazhuang 050024 China Guizhou Provincial Key Laboratory of Radio Astronomy and Data Processing Guizhou Normal University Guiyang 550001 China School of Physics and Optoelectronics Xiangtan University Yuhu District Xiangtan Hunan 411105 China School of Computer and Information Dezhou University Dezhou 253023 China

The second brightest gamma-ray burst (GRB) in history, GRB 230307A, provides an ideal laboratory to study the mechanism of GRB prompt emission thanks to its extraordinarily high photon statistics and its single-episode activity. Here we demonstrate that the rapidly variable components of its prompt emission compose an overall broad single pulse-like profile. Although these individual rapid components are aligned in time across all energy bands, this overall profile conspires to show a well-defined energy-dependent behavior that is typically seen in single GRB pulses. Such a feature demonstrates that the prompt emission of this burst is from many individual emitting units that are casually linked in a emission site at a large distance from the central engine. Such a scenario is in natural consistency with the internal-collision-induced magnetic reconnection and turbulence framework, which invokes many minijets due to local magnetic reconnection that constantly appear and disappear in a global magnetically dominated jet. © 2025. The Author(s). Published by the American Astronomical Society.

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A Resource Matching Algorithm for Dynamic Multi-Homing Service Environment 2

A Resource Matching Algorithm for Dynamic Multi-Homing Servi...

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2nd IEEE Advanced information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018

作者： Zhang, Hui Liu, Shu Nanjing University of Posts and Telecommunications Jiangsu Key Lab of Wireless Communications Nanjing China National Engineering Research Center of Communications and Networking Nanjing University of Posts and Telecommunications Nanjing210003 China Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou215006 China

ISBN: (纸本)9781538618035

T43 paper investigates the matching problem between radio resources and multi-homing services in a dynamic heterogeneous wireless environment. A mobile terminal (MT) with multi-homing service simultaneously transmits data to multiple radio access networks using multiple air interfaces. We develop an energy efficient resource matching algorithm for statistically guaranteeing the transmission rate of each MT with the minimum power consumption. Firstly, aided with the resource matching conception and the dynamic characteristics of wireless channels, we propose a matching probability metric to construct resource matching model for maximizing energy efficiency of all MTs subject to statistical guarantee requirements, and simplify the dynamic channels characteristic based on matching theory. Secondly, we propose a two-level distributed matching algorithm (TLDMA), with inner minimum power consumption and outer maximum matching probability, which realizes joint optimal allocation of bandwidth, transmission power and rate. Simulation results show that TLDMA outperforms conventional algorithms in terms of wireless resources management. © 2018 IEEE.

关键词： Energy efficiency

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UWB SAR image segmentation algorithm based on polynomial analysis of statistical distribution

UWB SAR image segmentation algorithm based on polynomial ana...

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Asian and Pacific Conference on Synthetic Aperture Radar (APSAR)

作者： Wang Yuming Jin Tian Luo Chaopeng College of Information Science and Engineering Hunan Provincial Key Laboratory of Intelligent Computhing and Language Information Processing Science and Technology on Near-Surface Detection Laboratory Hunan Normal University Changsha R.P.China College of Electronic Science and Technology Science and Technology on Near-Surface Detection Laboratory National University of Defense Technology Changsha R.P.China Science and Technology on Near-Surface Detection Laboratory Wuxi China

ISBN: (数字)9781728129129

ISBN: (纸本)9781728129136

Aimed at the segmentation problem of ultrawideband synthetic aperture radar (UWB SAR) image, a novel algorithm based on polynomial analysis of statistical distribution is proposed in this letter. Firstly, we estimate the probability density function (PDF) for each pixel via sparse decomposition of which the dictionary consists of orthogonal polynomials (OP). Secondly, the weighting coefficients of corresponding OP are used to segment image using their maximum value. The experimental results validate the efficiency of this algorithm.

关键词： Image segmentation Probability density function Synthetic aperture radar Radar polarimetry Signal processing algorithms Scattering Statistical distributions

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Service Deployment for Latency Sensitive Applications in Mobile Edge Computing

Service Deployment for Latency Sensitive Applications in Mob...

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International Conference on Advanced Cloud and Big Data (CBD)

作者： Jingya Zhou Jianxi Fan Jin Wang Juncheng Jia Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou China School of Computer Science and Technology Soochow University Suzhou China

Mobile edge computing (MEC) emerges as a promising computing paradigm to meet the increasing demand for compute-intensive latency-sensitive applications. By offloading tasks to the edge MEC can achieve many benefits such as ultra-low latency and saving backbone bandwidth, etc. Many studies have concentrated on the high efficient task offloading. However, the existing studies assume that tasks can be executed on an arbitrary edge server, but in reality different application's tasks require varied services to provide the execution environment and an edge server can host a limited number of services. How to determine the set of services deployed on each server in a MEC system is challenging. To address this challenge, in this paper, we focus on the problem of service deployment, and formulate the problem as a multi-slot latency minimization by leveraging the Lyapunov optimization. An efficient online algorithm is designed to minimize the average latency under a tight budget, and the supremum on algorithm performance is also presented. Experimental results indicate that our algorithm can reduce average latency for end users, and guarantee a low expenditure for the edge service provider.

关键词： Servers Task analysis Edge computing Cloud computing Bandwidth Heuristic algorithms Optimization

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Towards real-time eyeblink detection in the wild: Dataset, theory and practices

arXiv

引用

arXiv 2019年

作者： Hu, Guilei Xiao, Yang Cao, Zhiguo Meng, Lubin Fang, Zhiwen Zhou, Joey Tianyi Yuan, Junsong National Key Laboratory of Science and Technology on Multi-Spectral Information Processing School of Artificial Intelligence and Automation Huazhong University of Science and Technology China Guangdong Provincial Key Laboratory of Medical Image Processing School of Biomedical Engineering Southern Medical University China School of Energy and Mechanicalelectronic Engineering Hunan University of Humanities Science and Technology China Institute of High Performance Computing A∗STAR Singapore Computer Science and Engineering Department of University at Buffalo State University of New York United States

Effective and real-time eyeblink detection is of widerange applications, such as deception detection, drive fatigue detection, face anti-spoofing. Despite previous efforts, most of existing focus on addressing the eyeblink detection problem under constrained indoor conditions with relative consistent subject and environment setup. Nevertheless, towards practical applications, eyeblink detection in the wild is highly preferred, and of greater challenges. In this paper, we shed the light to this research topic. A labelled eyeblink in the wild dataset (i.e., HUST-LEBW) of 673 eyeblink video samples (i.e., 381 positives, and 292 negatives) is first established. These samples are captured from the unconstrained movies, with the dramatic variation on face attribute, head pose, illumination condition, imaging configuration, etc. Then, we formulate eyeblink detection task as a binary spatial-temporal pattern recognition problem. After locating and tracking human eyes using SeetaFace engine and KCF (Kernelized Correlation Filters) tracker respectively, a modified LSTM model able to capture the multi-scale temporal information is proposed to verify eyeblink. A feature extraction approach that reveals the appearance and motion characteristics simultaneously is also proposed. The experiments on HUSTLEBW reveal the superiority and efficiency of our approach. The comparisons with the existing state-of-the-art methods validate the advantages of our manner for eyeblink detection in the wild. Copyright © 2019, The Authors. All rights reserved.

关键词： Long short-term memory

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