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作者： He, Bei Liu, Gang Ji, Ying Si, Yongsheng Gao, Rui Key Laboratory of Modern Precision Agriculture System Integration Research Ministry of Education China Agricultural University Beijing 100083 China College of Information Science and Technology Agricultural University of Hebei Baoding 071001 China

ISBN: (纸本)9783642183324

An algorithm of generating navigation path in orchard for harvesting robot based on machine vision was presented. According to the features of orchard images, a horizontal projection method was adopted to dynamically recognize the main trunks area. Border crossing points between the tree and the earth were detected by scanning the trunks areas, and these points were divided into two clusters on both sides. Resorting to least-square fitting, two border lines were extracted. The central clusters were gained by the two lines and this straight line was regarded as the navigation *** simulation result shows that the algorithm could effectively extract navigation path in complex orchard environment, and correct recognition rate was 91.7%. The method is proved to be stable and reliable, and with the deviation rate of simulation navigation angle compared with the artificial recognition angle is around 2%. © 2011 IFIP International Federation for Information Processing.

关键词： Computer vision

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Inuence maximization algorithm based on genetic algorithm

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Journal of Computational Information systems 2014年第21期10卷 9255-9262页

作者： Guo, Jingfeng Liu, Yuanying Shen, Jiali Wei, Zhenzhen Lv, Jiaguo College of Information Science and Engineering Yanshan University Qinhuangda China College of Information Technology Hebei University of Economics and Business Shijiazhuang China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao China

The inuence maximization problem is defined as providing a given initial integer k, mining top-k inuential nodes from a social network such that the spread of inuence in the network is maximized. Some existing studies are based on Greedy algorithm, but their time complexity is very high. In this paper, a different method based on Genetic Algorithms, denoted as MAGA is proposed. In the MAGA algorithm, the set of k nodes is seen as a candidate solution, and the expected inuence value as fitness. Use the genetic algorithm to get the optimal solution. Experiments show that the algorithm achieved a balance in inuence spread and running time.

关键词： Genetic algorithms

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A Time-aware POI Recommendation Method Exploiting User-based Collaborative Filtering and Location Popularity

A Time-aware POI Recommendation Method Exploiting User-based...

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2017 2nd International Conference on Communications, Information Management and Network Security (CIMNS2017)

作者： Ya-li SI Fu-zhi ZHANG Wen-yuan LIU School of Information Science and Engineering Yanshan University School of Liren Yanshan University The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province

Point-of-interest(POI) recommendation becomes an important research for location-based social networks, since it helps modern citizens to explore new locations in unvisited cites effectively according to their preferences. However, the current POI recommendation methods are lack of a deep mining in all time slots features and their effects on recommendation. To this end, in this paper we propose a POI recommendation method(called UPT) by combining time slot features, user-based collaborative filtering and spatial influence. Firstly, we extract time interval feature and time slot based popularity feature from history check-in datasets on LBSNs using probability statistical analysis method. Then, we devise a POI recommendation method based on the proposed temporal features to achieve better performance. In UPT, user-based collaborative filtering and smoothing technique are used by adding each time slot influence, and the overall popularity of a location is combined with each time slot feature. Our experimental results on Foursquare and Gowalla datasets show that UPT outperforms baseline POI recommendation methods in precision and recall.

关键词： Location-based social networks Point-of-interest recommendation User-based collaborative filtering Location popularity Temporal feature

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An improved multiple target tracking method in the pigpen based on kernel correlation filter by thermal infrared video

An improved multiple target tracking method in the pigpen ba...

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2017 ASABE Annual International Meeting

作者： Maa, Li Liu, Gang Cai, Yixin Zong, Ze Key Laboratory of Modern Precision Agriculture System Integration Research Ministry of Education China Agricultural University Beijing100083 China College of Information Science and Technology Agricultural University of Hebei Baoding071001 China

The rapid turning movement of the pig often results in the tracking frame drift or loss of the target, resulting in reduced tracking accuracy. In this paper, an improved multi-objective KCF tracking algorithm is proposed using thermal infrared video as a video source. The tracking window is optimized to be rounded to avoid the effects of motion steering;the traditional KCF algorithm is improved so that it can achieve multiple pig target tracking. The experimental data are three videos containing two, three, and five pigs, respectively. A total of 90 videos, including pitching, walking, steering, adhesion, non-blocking and occlusion, were selected for testing, and the DCF and MOSSE algorithms were also improved to multi-target tracking. The results show that the improved tracking accuracy of MKCF algorithm is better than that of MDCF and MMOSSE, and the tracking time satisfies the requirement of real - time.

关键词： Target tracking

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Object Tracking by Jointly Utilizing Template Updating and Relocation Mechanisms⋆

SSRN

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SSRN 2023年

作者： Wen, Jia Ren, Kejun School of Information Science and Engineering Yanshan University Qinhuangdao066099 China The Key Laboratory for Computer Virtual Technology System Integration of Hebei Province China

The Siamese network-based tracker has achieved competitive performance in the field of single target tracking because of its excellent tracking speed and tracking accuracy. When faced with target deformations, most Siamese trackers rely on fixed template features from the initial frame, severely constraining the tracker’s performance. To mitigate this situation, we introduce a novel tracking framework(SiamTAR) that allows adaptive template updates based on past tracking information. In addition, we design a feature refinement module which can capture the target information more accurately at the full scale on the search image through an integrated attention mechanism, thus enabling the tracker to pay less attention to redundant information. Notably, we introduce a relocalization mechanism to solve the problems of random drift of the tracking box and inaccurate scale estimation in online tracking. Extensive experiments on GOT-10K, UAV123, OTB100 and DTB70 datasets show that the tracker achieves good tracking results and real-time performance. © 2023, The Authors. All rights reserved.

关键词： Target tracking

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The effects of DHPG stimulation on spikes and theta frequency oscillations and spike-theta oscillation relations in rat MSDB slice

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Journal of Convergence Information technology 2012年第17期7卷 442-449页

作者： Wen, Dong Ouyang, Gaoxiang Peng, Ce Li, Xiaoli Lu, Chengbiao Key Laboratory for Computer Virtual Technology and System Integration of HeBei Province Yanshan University Qinhuangdao Hebei China Institue of Electrical Engineering Yanshan University Qinhuangdao Hebei China National Key Laboratory of Cognitive Neuroscience and Learning Beijing Normal University Beijing 100088 China

Neuronal oscillations in the theta frequency range and spikes have been reported in many cortical areas in the information processing, but the role of spikes play in cortical processing remains unclear. The aim of this study was to examine the role of DHPG in the generation of oscillatory field activity at theta frequency in the medical septal diagonal band of Broca (MSDB) slice prepared from rat brain, and to determine the phase relationship between spikes and theta oscillations. The DHPG induced large amplitude field population spiking activity, which is correlated linearly with the field theta oscillations. The relationship between timing of spikes and the phase of theta oscillation was determined by an analysis of circular statistics. Further analysis with Rayleigh test revealed that the relationship of phase-locking between spikes and theta rhythm is of statistical significance. These data demonstrate that DHPG-sensitive neuronal networks within medial septum are able to generate theta oscillations which are modulated by large amplitude population spikes and phase-locking of spikes to the theta rhythm suggest the role of memory enhancement in the presence of mGluR1 activation.

关键词： Rats

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An algorithm based on bit complementary tree for mining closed frequent itemsets

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International Journal of Advancements in Computing technology 2012年第22期4卷 427-435页

作者： Ren, Jiadong Yang, Xuan Dong, Jun College of Information Science and Engineering Yanshan University Qinhuangdao City066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao City 066004 China

In recent years, closed frequent itemsets mining has become a hot topic. In this paper, we present an algorithm BCTCF, which is based on Bit complementary tree (BCTree) in order to mine closed frequent itemsets efficiently. First we adopt bit vectors to compress the database and define a novel structure, BCTree, in which a node stores two bit vectors that are complementary and each path is given a prime value. Based on the left-most bit in the bit vectors we adopt a divide-and-conquer strategy which handles the itemsets separately and then according to the prime unique feature we can get the closed frequent itemsets quickly and it makes us need not to mine all the frequent itemsets first. Both the divide-and-conquer strategy and prime unique can decrease the runtime. Experiment results show that BCTCF is very effective and scalable.

关键词： Forestry

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Mining the important nodes of software based on complex networks

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ICIC Express Letters 2015年第12期9卷 3263-3268页

作者： Huang, Guoyan Zhang, Peng Li, Yanling Ren, Jiadong College of Information Science and Engineering Yanshan University No. 438 Hebei Ave Qinhuangdao China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University No. 438 Hebei Ave Qinhuangdao China

The main purpose of studying the software structure is considered to understand and recognize the structure easily by also taking into account the quality of software. In this paper, we define and analyze the node importance based on the invoking dependency relationships among the nodes to mine the influential nodes for the software. Firstly, we construct a directed network to denote the software execution process depending on the invoking relationships. Secondly, according to the information of the Dependency Node Set (DNS) of each function node, we define the importance for the node. Finally, we present the algorithm Measure the Importance of Node (MIN) to evaluate the importance of each node. Comparing the value of nodes by the algorithm Mining the top-K Nodes (MKN), we can obtain the most influential nodes in the software network. In addition, with experiments results, the method MKN is verified to be effective for measuring the importance of the function nodes accurately. © 2015 ICIC International.

关键词： Complex networks

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A clustering algorithm for data stream based on spatial directed graph with core

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Journal of Convergence Information technology 2012年第19期7卷 131-139页

作者： Dong, Jun Yuan, Xuemei Ren, Jiadong College of Information Science and Engineering Yanshan University Qinhuangdao City 066004 China Key Laboratory for Computer Virtual Technology System Integration of Hebei Province Qinhuangdao City 066004 China

Due to the randomness of the partition of grids, the edge points of clusters might be partitioned into the sparse grids. These points would become noise information out of clusters when we cluster data stream by grid-density based algorithm. A data stream clustering algorithm based on spatial directed graph with core, SDGCStream, is proposed. It uses the spatial directed graph and the orthocenter of the sparse grids to handle the edge points of clusters. At first, the algorithm defines a structure SDGC (Spatial Directed Graph with Core) to store the summary statistics of data stream. The vertices of SDGC are maintained as the stream arriving. When the clustering quest comes, the edge information is generated. The initial clustering results are got through clustering on SDGC, then we judge whether the points of sparse grids which are adjacent to the border of a cluster belong to the cluster according to the orthocenter information and the border vertices of SDGC. At last, a strategy based on the distance between clusters is presented to adjust the clustering results after handling the border of clusters. The experimental results on synthetic and real datasets show the better validity of SDGCStream on handling the edge data points of clusters, and the scalability as the increasing of the length and dimensions of data stream.

关键词： Clustering algorithms

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Mining software behavior pattern from software execution trace

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ICIC Express Letters, Part B: Applications 2015年第12期6卷 3367-3372页

作者： Ren, Jiadong Wu, Hongfei Yin, Tengteng Li, Yanling Liu, Jiaxin Dong, Jun College of Information Science and Engineering Yanshan University No. 438 Hebei Avenue Qinhuangdao066004 China The Key Laboratory for Computer Virtual Technology System Integration of Hebei Province No. 438 Hebei Avenue Qinhuangdao066004 China

A software execution trace can be viewed as a series of events. An event may correspond to the execution of a basic block, the invocation of a class or a method. These traces imply important unique characteristics of software behaviors. In this paper, a novel approach to mine representative software behavior patterns is proposed. First, we give an exact definition of Common Closed Ordered Iterative Pattern (CCOIP). The pattern may occur many times not only within a single trace but also across multiple traces. Then, an efficient algorithm called CCOIP-Miner is proposed to mine CCOIP. The mined CCOIPs are regarded as representative software behavior patterns. Our experiment results show the efficiency of algorithm CCOIP-Miner. © 2015, ICIC Express Letters Office. All rights reserved.

关键词： Miners

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