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International Symposium on Computer Science and Computational Technology, ISCSCT

作者： Shangfei Wang Siliang Lv Xufa Wang Department of Computer Science and Technology Key Laboratory of Software Computing and Communication Anhui University of Science and Technology Hefei Anhui China

Since infrared images reflect the temperature-field distributing of vein¿s embranchment of the face, expression recognition from them should focus on changes of thermal distribution on facial muscles and blood vessels, which caused by mood variety. These thermal changes can be regarded as texture features of images. Wavelet transform is a good tool to analyze multi-scale, multi- direction changes of texture. Therefore, this paper presented a facial expression recognition method from thermal images using wavelet transform. Firstly, the status quo of the researches on infrared facial expression recognitions was briefly surveyed and analyzed. Secondly, wavelet transforms were used to extract image features. Thirdly, the ¿Euclidian Distance Maximizing Method¿ we proposed was adopted to select features. Then principal component analysis was employed to reduce feature dimension and NN was used as a classifier. Finally, experiments on medium-wave thermal facial expressions database of Equinox evaluated the effectiveness of our approach.

关键词： Face recognition Wavelet transforms Image recognition Infrared imaging Emotion recognition Facial muscles Blood vessels Biomedical imaging Mood Wavelet analysis

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TCPModel: A short-term traffic congestion prediction model based on deep learning 2nd

TCPModel: A short-term traffic congestion prediction model b...

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2nd CCF International Conference on Artificial Intelligence, CCF-ICAI 2019

作者： Xu, Xiujuan Gao, Xiaobo Xu, Zhenzhen Zhao, Xiaowei Pang, Wei Zhou, Hongmei School of Software Dalian University of Technology Dalian116620 China Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province Dalian116620 China School of Natural and Computing Sciences University of Aberdeen AberdeenAB24 3UE United Kingdom School of Transportation and Logistics Dalian University of Technology Dalian116024 China

ISBN: (纸本)9789813292970

With the progress of the urbanization, a series of traffic problems have occurred because of the growing urban population and the far lower growth rate of roads than that of cars. One of the most prominent problems is traffic congestion problem. The prediction of traffic congestion is the key to alleviate traffic congestion. To ensure the real-time performance and accuracy of the traffic congestion prediction, we propose a short-term traffic congestion prediction model called TCPModel based on deep learning. By processing a massive amount of urban taxi transportation data, we extract the traffic volume and average speed of taxis which are the most important parameters for assessing of traffic flow prediction. After analyzing the temporal and spatial distribution characteristics of the traffic flow and average speed, we present a short-term traffic volume prediction model called TVPModel, and a short-term traffic speed prediction model called TSPModel. Both models are based on a deep learning method Stacked Auto Encoder (SAE). By comparing the other traffic flow forecasting methods and average speed forecasting methods, the methods proposed by this paper have improved the accuracy rate. For traffic congestion recognition, we use a novel model called TCPModel based on three traffic parameters (average speed, traffic flow and density), which uses standard function method to standardize the parameters and calculate the congestion comprehensive threshold to determine the congestion level by thresholds. According to the experiments, TVPModel and TSPModel in this paper got satisfied accuracy compared with other prediction models. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Traffic congestion

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A qualitative modeling and simulation method based on cloud model

A qualitative modeling and simulation method based on cloud ...

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International Conference on Modeling, Simulation and Applied Optimization (ICMSAO)

作者： Chenxi Shao Kelü Sun Zhenzhong Shao Computer Science and Technology Department University of Science and Technology of China Hefei China Anhui Province Key Laboratory of Software in Computing and Communication Hefei China Jianghuai Automobile Company Limited Hefei China

ISBN: (纸本)9781467358125

Qualitative simulation is effective methods processing incomplete knowledge, how to represent qualitative knowledge and reduce spurious behaviors is its research emphasis. Contraposing the limitations of existing methods representing qualitative knowledge and filtering spurious behaviors, an approach is proposed to qualitatively model and simulate on the basis of normal cloud model. In this research, the cloud numeric characteristics and cloud measurement are introduced into this approach; consequently, it can more accurately assess the qualitative knowledge, and expand the variables expression and quantity space; meanwhile, it is constructed the means of modeling and simulation by adopting more amply portraying the system status, more intuitively transforming status and more accurately filtering spurious behaviors. Furthermore, in simulation algorithm, cloud measurement indices are employed to significantly select the successor status which can not be determined by existing constraint means. The results of simulation example demonstrate that our approach effectively improves the ability to filter spurious behaviors, and it is a feasible method.

关键词： Uncertainty Coordinate measuring machines Computational modeling Entropy Measurement uncertainty Numerical models Size measurement

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Airborne moving vehicle detection for urban traffic surveillance

Airborne moving vehicle detection for urban traffic surveill...

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International Conference on Intelligent Transportation

作者： Renjun Lin Xianbin Cao Yanwu Xu Chuangxian Wei Hong Qiao Anhui Province Key Laboratory of Software Computing and Communication University of Science and Technology Hefei China University of Manchester Institute of Science and Technology UK Institute of Automation Chinese Academy and Sciences Beijing China

At present, moving vehicle detection on airborne platform has been an important technology for urban traffic surveillance. In such a situation, most commonly used methods (e.g. image subtraction) could hardly work well because of some additional difficulties such as slow movement of vehicles and jam. This paper proposed a new moving vehicle detection method named MVD-RD for airborne urban traffic surveillance. First, the non-road regions are extracted using road detection technique. Secondly, the non-road regions with no vehicles are removed according to their size. As a result of this two-stage regions shrinkage, the detection area reduces a lot. Finally, to the reduced area, image subtraction is used to get all moving regions and then moving vehicles can be accurately filtered in a simple way. The experimental results show that, compared with traditional image subtraction methods used in airborne moving vehicle detection, the proposed MVD-RD method achieves much better performance in detection rate, false alarm rate, and detection speed.

关键词： Vehicle detection Surveillance Road vehicles Cameras Road transportation Layout Intelligent transportation systems Optical filters Intelligent vehicles Air transportation

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Spontaneous Facial Expression Recognition Based on Feature Point Tracking

Spontaneous Facial Expression Recognition Based on Feature P...

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International Conference on Image and Graphics (ICIG)

作者： Shan He Shangfei Wang Yanpeng Lv Key Laboratory of Computing and Communicating Software of Anhui Province School of Computer Science and Technology University of Science and Technology Hefei Anhui China

In recent years, facial expression recognition has attracted a lot of attention because of its importance in human-computer interaction. However, most previous work has focus on posed expression. In this paper, we propose a spontaneous facial expression recognition method based on feature point tracking. First, all expression sequences are normalized according to their pupils' coordinates. Second, 23 points are labeled manually in the onset and apex frames. Then Kalman filter is used for tracking. Two kinds of features, point displacement features and points distance variation features, are extracted. Finally, Hidden Markov Model is employed as classifier. Experiments have been conducted on the spontaneous facial expression database of USTC-NVIE. The results indicate that Kalman filter point tracking method could detect the right place of points, and the points distance variation features are more suitable than the point displacement features for the facial expression recognition.

关键词： Feature extraction Kalman filters Hidden Markov models Tracking Head Accuracy Face recognition

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Fast Collection of Target Tags Information for Large-Scale RFID Systems 20

Fast Collection of Target Tags Information for Large-Scale R...

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20th International Computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2023

作者： Chu, Chu Fu, Ning Xu, Rui College of Computer Science Sichuan Normal University Chengdu610101 China The Visual Computing and Virtual Reality Key Laboratory of Sichuan Province Chengdu610101 China School of Network and Communication Engineering Chengdu Technological University Chengdu611730 China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China

ISBN: (纸本)9798350318982

Radio Frequency Identification (RFID) technology is greatly supporting a variety of life and industry. Enhanced by sensors, RFID tags can monitor real-time information about attached objects and the environment, making efficient collection of tag information an important task. However, most works focus on collecting all tags but lack effective mechanisms to avoid interfering from irrelevant tags when the application only cares about a part of the tags in some cases. Besides, in more common scenarios with multiple RFID readers, existing works fail to effectively determine the surrounding tags for each reader, increasing the execution time. To conquer these defects, we propose a new solution called the efficient Vector-based target tag Information Collection (VIC) protocol to accelerate the collection rate. First, we introduce a composite vector to silence irrelevant tags and determine the local tags. During this process, the expected empty slots are skipped and the useless information transmitted by tags is reduced. Second, we use an allocation vector to collect tag information by resolving tag collision, thus improving the time efficiency. Finally, we provide theoretical analyses to optimize the parameter settings. Extensive experiments prove that VIC outperforms existing solutions by up to 32% increase in time efficiency. © 2023 IEEE.

关键词： Efficiency

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Constructing the Voronoi Diagram of Planar Point Set in Parallel

Constructing the Voronoi Diagram of Planar Point Set in Para...

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International Conference on Computational Intelligence and software Engineering (CiSE)

作者： Lanfang Dong Yuan Wu Shanhai Zhou Anhui Province Key Laboratory of Software In Computing and Communication College of computer science and technology University of Science and Technology Hefei China College of computer science & technology University of Science and Technology Hefei China

By researching Voronoi diagram, parallel algorithm, and divide-and-conquer method, we present a special data structure(change doubly-connected list little) for Voronoi diagram generation in parallel. In this paper we also present two proposal, they are one processor gradually to merge and 22-merger on the parallel machine, the experiment results show that the present algorithm runs faster than the serial program. By analyzing the various results, we should choose the most suitable number of processors according to the point set scale. At last, we can conclude that gradually merger with one processor is better proposal for Voronoi diagram parallel generation.

关键词： Data structures Educational institutions Computer science Parallel algorithms Proposals Switches Merging Concurrent computing Parallel machines Geography

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An Evolutionary Support Vector Machines Classifier for Pedestrian Detection

An Evolutionary Support Vector Machines Classifier for Pedes...

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2006 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： D. Chen X.b. Cao Y.w. Xu H. Qiao Department of Computer Science and Technology University of Science and Technology Hefei China Anhui Province Key Laboratory Software Computing and Communication Hefei China Institute of Automation Chinese Academy and Sciences Beijing China

In a pedestrian detection system, a classifier is usually designed to recognize whether a candidate is a pedestrian. Support vector machines (SVM) has become a primary technique to train a classifier for pedestrian detection. However, it is hard to give the best training model which has a tremendous effect to the performance of a SVM classifier. In this paper, we design special code/decode scheme and evaluation function for a training model firstly; and then use genetic algorithm to optimize key parameters which represent the SVM training model. Therefore a most suitable SVM classifier can be obtained for pedestrian detection. Experiments have been carried out in a single camera based pedestrian detection system. The results show that the evolutionary SVM classifier has a better detection rate; moreover, RBF kernel is more suitable than polynomial kernel when chosen in an evolutionary SVM classifier for pedestrian detection

关键词： Support vector machines Support vector machine classification Kernel Genetic algorithms Decoding Design optimization Cameras Intelligent robots Computer science Laboratories

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Research on cloud computing complex adaptive agent

Research on cloud computing complex adaptive agent

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International Conference on Services Systems and Services Management, ICSSSM

作者： Qingyi Chen Hongwei Kang Hua Zhou Xingping Sun Yong Shen YunZhi Jin Jun Yin Cloud computing research center of Yunnan China School of Software Yunnan University Kunming Yunnan China Key Laboratory for Software Engineering of Yunna Province Republic of China

It has gradually realized in the industry that the increasing complexity of cloud computing under interaction of technology, business, society and the like, instead of being simply solved depending on research on information technology, shall be explained and researched from a systematic and scientific perspective on the basis of theory and method of a complex adaptive system (CAS). This article, for basic problems in CAS theoretical framework, makes research on definition of an active adaptive agent constituting the cloud computing system, and proposes a service agent concept and basic model through commonality abstraction from two basic levels: cloud computing technology and business, thus laying a foundation for further development of cloud computing complexity research as well as for multi-agent based cloud computing environment simulation.

关键词： Cloud computing Computational modeling Adaptive systems Complexity theory Business Adaptation models Economics

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A mesh editing algorithm based on Gaussian curvature

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Journal of Information and Computational Science 2013年第10期10卷 2881-2890页

作者： Wang, Feng Huang, Zhangjin Guo, Licai School of Computer Science and Technology University of Science and Technology of China Hefei 230027 China Key Laboratory of Software in Computing and Communication Hefei 230027 China USTC-SICT Joint Laboratory on Network and Communication Hefei 230027 China

Mesh editing plays an important role in the design of mesh models. The As-Rigid-As-Possible (ARAP) surface editing algorithm is likely to produce degenerated results in sharp regions. This degeneration affects the quality of results. This paper proposes a new mesh editing algorithm based on the ARAP surface modeling algorithm. By setting constraints on triangle transformations, this algorithm has better detail-preserving properties. With the constraints on the ratios among scaling factors, we can reduce the skinny triangles produced by the ARAP algorithm. The experimental results showed that this algorithm improved robustness and detail-preservation over the As-Rigid-As-Possible algorithm. Copyright © 2013 Binary Information Press.

关键词： Mesh generation

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