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A Web-Based Theme-Related Word Set Construction Algorithm

A Web-Based Theme-Related Word Set Construction Algorithm

引用

Asia Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint Conference on Web and Big Data, APWeb-WAIM 2018

作者： Wu, Yingkai Li, Yukun Hao, Gang Tianjin University of Technology Tianjin300384 China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin China Key Laboratory of Computer Vision and System Ministry of Education Tianjin Tianjin China

ISBN: (纸本)9783030012977

Constructing theme-related word set is a basic work for establishing theme-oriented information retrieval systems. Nowadays, most of previous studies focus on identifying representative words of a specific document, and few studies pay attention to constructing a word set related to a theme. By analyzing existing keywords extraction methods, this paper proposes a method to automatically construct theme-related word set based on the primary theme-related word set given by domain experts and the well-known websites related to the theme. As the first step, the method uses existing information extraction techniques to obtain the documents from the websites and every document’s keyword set. Then it calculates the correlation degree between the known theme-related word set and the document keyword set, further gets a word set of the document related to the theme based on the document-theme relevance, and merges the word set to the theme-related word set. By using the method, the theme-related word set is supplemented by iteration based on the documents gotten from the theme-related websites. Because there is little research work focusing on this problem and no relevant experimental data set, this paper uses the proposed method to construct theme-related word sets towards two themes "electricity" and "college entrance examination", and we invite domain experts to evaluate the word sets. The results show that a relatively complete theme-related word set can be obtained based on this method, which shows the feasibility of our methods. © 2018, Springer Nature Switzerland AG.

关键词： Websites

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A method of genetic algorithm optimized extended kalman particle filter for nonlinear system state estimation

A method of genetic algorithm optimized extended kalman part...

引用

5th International Conference on Natural Computation, ICNC 2009

作者： Yang, Shuying Huang, Wenjuan Ma, Qin Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology 300191 Tianjin China Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin 300191 China

ISBN: (纸本)9780769537368

A new method of genetic algorithm (GA) optimized the extended kalman particle filter (EKPF) is proposed in this paper. The algorithm of extended kalman particle filter is a suboptimal filtering algorithm with good performance for target tracking and non-linear tracking problem. In the implementation of the extended kalman particle filter, a resampling scheme is used to decrease the degeneracy phenomenon and improve estimation performance. However, the target tracking mutation system status has poorer filtering precision. In order to overcome the problem of the extended kalman particle filter, a novel filtering method called the genetic particle filter (GA-EKPF) is proposed in this paper. The genetic mechanism provides an important guiding ideology to solve the deprivation of particles. The proposed algorithm overcomes the deprivation of particles and enhances the filtering precision. Experimental results show that the performance of modified extended kalman particle filter superiors to the standard particle filter (PF) and some other modified PFs. © 2009 IEEE.

关键词： Genetic algorithms

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Pose-guided feature region-based fusion network for occluded person re-identification

Pose-guided feature region-based fusion network for occluded...

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作者： Xie, Gengsheng Wen, Xianbin Yuan, Liming Wang, Jianchen Guo, Changlun Jia, Yansong Li, Minghao School of Computer Science and Engineering Tianjin University of Technology Tianjin300384 China Key Laboratory of Computer Vision and System Ministry of Education Tianjin300384 China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin300384 China

Learning distinguishing features from training datasets while filtering features of occlusions is critical to person retrieval scenarios. Most of the current person re-identification (Re-ID) methods based on classification or deep metric representation learning tend to overlook occlusion issues on the training set. Such representations from obstacles are easily over-fitted and misleading due to being considered as a part of the human body. To alleviate the occlusion problem, we propose a pose-guided feature region-based fusion network (PFRFN), to utilize pose landmarks as guidance to guide local learning for a good property of local feature, and the representation learning risk is evaluated on each part loss separately. Compared with only using global classification loss, concurrently considering local loss and the results of robust pose estimation enable the deep network to learn the representations of the body parts that prominently displayed in the image and gain the discriminative faculties on occluded scenes. Experimental results on multiple datasets, i.e., Market-1501, DukeMTMC, CUHK03, demonstrate the effectiveness of our method in a variety of scenarios. © 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature.

关键词： Classification (of information)

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A multi-scale-based super-resolution method for face image

A multi-scale-based super-resolution method for face image

引用

2010 3rd International Congress on Image and Signal Processing, CISP 2010

作者： Zhang, Simiao Zhang, Hua Zhang, Lan Xue, Yanbing Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology 300191 Tianjin China Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology 300191 Tianjin China

ISBN: (纸本)9781424465149

We propose a new algorithm about multi-scale-based super-resolution on face image. First, steerable pyramid is used to capture low-level local features in face images, and then these features are combined with pyramid-like parent structure and image patch synthetic approach based on neighborhood to predict the best prior. After that, the prior is integrated into Bayesian maximum a posteriori (MAP) framework. Finally, the optimal high-resolution face image is obtained by a global linear smoothing operator. It is can be seen from the experimental result that oriented facial features in the high-resolution face are recovered well. The most crucial is that our algorithm significantly reduces the computational complexity. ©2010 IEEE.

关键词： Optical resolving power

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An improved RED congestion algorithm based on partition of network segment

An improved RED congestion algorithm based on partition of n...

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5th International Conference on Natural Computation, ICNC 2009

作者： CtandongWang Li, Ting Wang, Huaibin Tianjin Key Laboratory of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin 300191 China Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin 300191 China

ISBN: (纸本)9780769537368

Aiming at the growing problem of network congestion, an improved random early detection algorithm is proposed for the internal network and applied on a TCP congestion control algorithm based on partition of network segment. By using known network information and network topology information, the method is more effective, and better results are achieved. © 2009 IEEE.

关键词： Network topology

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Genetic algorithm based on sugeno integral

Genetic algorithm based on sugeno integral

引用

6th International Conference on Fuzzy systems and Knowledge Discovery, FSKD 2009

作者： Wu, Zhilong Song, Jinjie Zhang, Caipo Tianjin Key Laboratory of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin 300191 China Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin 300191 China

ISBN: (纸本)9780769537351

For the actual need of future research and application, this paper proposes a new method that is a new fuzzy control system of fuzzy integral-genetic algorithm (FIGA). By fuzzy integral, it can study comprehensive evaluation of population diversity and individual quantity on three attributes: individual difference extent, the difference extent of individual's fitness and the difference extent of population lifetime, thereby dynamically adjust the rate of crossover (Pc) and mutation rate (Pm) in genetic algorithm. It improves the controller of fuzzy control for parameters Pc and Pm of genetic algorithm. The results of experiment show that the proposed genetic algorithm, combining fuzzy measure and fuzzy integral, performances better than simple genetic algorithm (SGA). © 2009 IEEE.

关键词： Genetic algorithms

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A Short-term Aircraft Trajectory Prediction Framework Using Conditional Generative Adversarial Network 4

A Short-term Aircraft Trajectory Prediction Framework Using ...

引用

4th IEEE International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2022

作者： Hu, Qinzhi Huang, Guoxin Shi, Han Lin, Yi Guo, Dongyue National Key Laboratory of Air Traffic Control Automation System Technology College of Computer Science Sichuan University Chengdu China National Key Laboratory of Fundamental Science on Synthetic Vision Sichuan University Chengdu China

ISBN: (数字)9781665467667

ISBN: (纸本)9781665467667

Short-term aircraft trajectory prediction (TP) plays an important role in current air traffic control systems. However, existing works usually perform the multi-horizon TP task in an iterated manner which easily suffers from error accumulation problems. In this work, a novel short-term aircraft TP framework, called TPGAN, is proposed which predicts the multi-horizon trajectory in a single step using the conditional generative adversarial network (CGAN). Compared with the conventional approaches, the TP task is formulated to the probability distribution estimate problems by CGAN architecture. In this framework, the generator is employed to output the predictions while the discriminative features between ground truth and predictions are learned by the discriminator. The generative adversarial training strategy is applied to optimize the proposed framework. Moreover, to validate the generality and effectiveness of the proposed framework, three neural network architectures are designed to develop the proposed framework, including Conv1D-TPGAN, Conv2D-TPGAN, and LSTM-TPGAN. In addition, a dataset collected from real-world ATC systems is used to construct the experiments. The experimental results demonstrated that the proposed framework achieves significantly performance improvements than baseline. © 2022 IEEE.

关键词： Air traffic control

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Parameter selection of support vector regression machine based on differential evolution algorithm

Parameter selection of support vector regression machine bas...

引用

6th International Conference on Fuzzy systems and Knowledge Discovery, FSKD 2009

作者： Yu, Qing Liu, Ying Rao, Feng Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology 300191 Tianjin China Key Laboratory of Computer Vision and System Tianjin University of Technology Ministry of Education 300191 Tianjin China

ISBN: (纸本)9780769537351

This parameters selection is an important issue in the research of Ε -support vector regression machine (Ε -SVRM), whose nature is an optimization selection process. Motivated by the effectiveness of Differential Evolution (DE) algorithm on optimization problem, a new automatic searching method based on DE algorithm was proposed. Experimental results demonstrate that Ε -SVRM model optimization based on DE algorithm has better prediction capability compared with the methods based on Genetic Algorithm (GA), Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). © 2009 IEEE.

关键词： Ant colony optimization

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A novel super-resolution image reconstruction based on MRF

A novel super-resolution image reconstruction based on MRF

引用

2009 2nd International Congress on Image and Signal Processing, CISP'09

作者： Yanjie, Ma. Zhang, Hua Yanbing, Xue Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin 300191 China Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin 300191 China

ISBN: (纸本)9781424441310

We address a novel method for super resolution based on Markov random field (MRF). Modeling image patches as MRF node, and we learn the parameters from training samples. Training sample set provide a candidate high-resolution interpretation for the low-resolution images. Given a new low-resolution image to enhance, we select from the training data a set of 10 candidate high-resolution patches for each patch of low-resolution image. In Bayesian belief propagation, we use compatibility relationships between neighboring candidate patches to select the most probable high-resolution candidate. The experimental results show that this method can obtain the better result. ©2009 IEEE.

关键词： Belief propagation

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Reverse testing image set model based multi-view human action recognition 22nd

Reverse testing image set model based multi-view human actio...

引用

22nd International Conference on MultiMedia Modeling, MMM 2016

作者： Gao, Z. Zhang, Y. Zhang, H. Xu, G.P. Xue, Y.B. Key Laboratory of Computer Vision and System Tianjin University of Technology Ministry of Education Tianjin300384 China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin300384 China

ISBN: (纸本)9783319276700

Recognizing human activities from videos becomes a hot research topic in computer vision, but many studies show that action recognition based on single view cannot obtain satisfying performance, thus, many researchers put their attentions on multi-view action recognition, but how to mine the relationships among different views still is a challenge problem. Since video face recognition algorithm based on image set has proved that image set algorithm can effectively mine the complementary properties of different views image, and achieves satisfying performance. Thus, Inspired by these, image set is utilized to mine the relationships among multi-view action recognition. However, the studies show that the sample number of gallery and query set in video face recognition based on image set will affect the algorithm performance, and several ten to several hundred samples is supplied, but, in multi-view action recognition, we only have 3–5 views (samples) in each query set, which will limit the effect of image set. In order to solve the issues, reverse testing image set model (called RTISM) based multi-view human action recognition is proposed. We firstly extract dense trajectory feature for each camera, and then construct the shared codebook by k-means for all cameras, after that, Bag-of-Word (BoW) weight scheme is employed to code these features for each camera;Secondly, for each query set, we will compute the compound distance with each image subset in gallery set, after that, the scheme of the nearest image subset (called RTIS) is chosen to add into the query set;Finally, RTISM is optimized where the query set and RTIS are whole reconstructed by the gallery set, thus, the relationship of different actions among gallery set and the complementary property of different samples among query set are meanwhile excavated. Large scale experimental results on two public multi-view action3D datasets - Northwestern UCLA and CVS-MV-RGBD-Single, show that the reconstruction of query

关键词： Cameras

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