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International Conference on Asian Language processing (IALP)

作者： Kong Fang Yancui Li Guodong Zhou Qiaoming Zhu Jiangsu Provincial Key Lab for Computer Information Processing Technology School of Computer Science and Technology Soochow Univ. Suzhou China College of Information Technology Henan Institute of Science and Technology Xinxiang Henan China Jiangsu Provincial Key Lab. for Comput. Inf. Process. Technol. Soochow Univ. Suzhou Suzhou China

This paper proposes to use a convolution kernel over parse tree to model syntactic structure information for pronoun resolution. Our study reveals that the syntactic structure features embedded in a parse tree are very effective for pronoun resolution and these features can be well captured by the context-sensitive convolution tree kernel. Evaluation on the ACE 2003 corpus shows that among all structured syntactic feature space, shortest path tree achieves the best performance. Then we incorporate more features into SPT, result shows that SPT can use successfully with normal features. Finally, we compare our system with other pronoun resolution systems, our results are outstanding in success rate than normal features and tree kernel-based method of Yang.

关键词： Convolution Kernel information processing computer science Educational institutions information technology Paper technology Electronic mail Data mining lab.ling

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Application of learning Vector quantization network on web pages classification in agricultural website

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Journal of information and Computational Science 2009年第1期6卷 139-145页

作者： Fu, Zetian Wang, Chuanyi Zhao, Ming Liu, Lixin Zhang, Xiaoshuan China Agricultural University Beijing 100083 China Jiangsu Provincial Key Laboratory of Computer Information Processing Technology Suzhou University Suzhou 215000 China

VQ (Learning Vector Quantization) is kind of supervised and competitive learning artificial neural network and adopted in many domains, such as pattern categorization, products classification, mechanical detection. This paper proposes a new application, which integrates LVQ network with Central Vector classification method on agricultural products web pages classification as key function of the vertical search engine. The experiment shows that LVQ has higher precision compared with CPN network and the precision increases more quickly with the increasing of training numbers. © 2009 Binary information Press.

关键词： Websites

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An evolution-based robust social influence evaluation method in Online Social Networks

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8787卷 141-157页

作者： Zhu, Feng Liu, Guanfeng Liu, An Zhao, Lei Zhou, Xiaofang School of Computer Science and Technology Jiangsu Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou215006 China School of Information Technology and Electrical Engineering University of Queensland Brisbane4072 Australia

Online Social Networks (OSNs) are becoming popular and attracting lots of participants. In OSN based e-commerce platforms, a buyer’s review of a product is one of the most important factors for other buyers’ decision makings. A buyer who provides high quality reviews thus has strong social influence, and can impact a large number of participants’ purchase behaviours in OSNs. However, the dishonest participants can cheat the existing social influence evaluation models by using some typical attacks, like Constant and Camouflage, to obtain fake strong social influence. Therefore, it is significant to accurately evaluate such social influence to recommend the participants who have strong social influences and provide high quality product reviews. In this paper, we propose an Evolutionary-Based Robust Social Influence (EB-RSI) method based on the trust evolutionary models. In our EB-RSI, we propose four influence impact factors in social influence evaluation, i.e., Total Trustworthiness (TT), Fluctuant Trend of Being Advisor (FTBA), Fluctuant Trend of Trustworthiness (FTT) and Trustworthiness Area (TA). They are all significant in the influence evaluation. We conduct experiments onto a real social network dataset Epinions, and validate the effectiveness and robustness of our EB-RSI by comparing with state-of-the-art method, SoCap. The experimental results demonstrate that our EB-RSI can more accurately evaluate participants’ social influence than SoCap. © Springer International Publishing Switzerland 2014.

关键词： Social networking (online)

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Video Object Tracking Method Based on Normalized Cross-correlation Matching

Video Object Tracking Method Based on Normalized Cross-corre...

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International Symposium on Distributed Computing and Applications to Business, Engineering and Science (DCABES)

作者： Jian Wu Heng-jun Yue Yan-yan Cao Zhi-ming Cui Provincial Key Laboratory of Computer Information Processing Technology Soochow University Suzhou China Soochow University Suzhou Jiangsu CN

Combing with specific temporal information of video, this paper proposes a kind of video object tracking method based on normalized cross-correlation matching by using the high precision characteristics of normalized cross-correlation image matching. Firstly, extract video background from the temporal information of video. Then, acquire the region of moving object using background subtraction. Lastly, carry out related matching and updating towards the extracted moving object by means of normalized cross-correlation. Experimental result shows that the adaptability of our method is strong, which can well solve the tracking problems when tracking objects have scale transform. It also has good anti-interference ability and robustness, and can track moving objects accurately under the condition of noise interference, lens dithering and background mutation.

关键词： Target tracking Noise Correlation Pixel Vehicles Cameras

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Data-consistent Unsupervised Diffusion Model for Metal Artifact Reduction

Data-consistent Unsupervised Diffusion Model for Metal Artif...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Tong, Zhan Wu, Zhan Yang, Yang Mao, Weilong Wang, Shijie Li, Yinsheng Chen, Yang Southeast University Laboratory of Image Science and Technology Nanjing210096 China Southeast University Ministry of Education Key Laboratory of Computer Network and Information Integration Nanjing210096 China Chinese Academy of Sciences Research Center for Medical Artificial Intelligence Shenzhen Institutes of Advanced Technology Shenzhen518055 China School of Computer Science and Engineering Key Lab. of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing The Laboratory of Image Science and Technology Nanjing210096 China

ISBN: (纸本)9798350337488

Computed Tomography (CT) is an imaging technique widely used in clinical diagnosis. However, high-attenuation metallic implants result in the obstruction of low-energy Xrays and further lead to metal artifacts in the reconstructed CT images. Deep supervised model-based metal artifact reduction(MAR) approaches are limited in clinical applications due to the difficulty in obtaining paired artifact-affected and artifactfree data. Furthermore, these model-based methods lack the consideration of data consistency in the sinogram-domain to perform exact metal trace inpainting. To address these challenges, we propose a Data-consistent unsupErVised diffusiOn model for meTal artifact rEDuction, called DEVOTED-Net. First, DEVOTED-Net leverages prior knowledge to guide the conditional diffusion model for fine-grained metal trace inpainting. Second, an unsupervised MAR framework is designed in the reverse process for the unknown metal traces restoration in the sinogram domain. Third, to further enhance the sinogram-domain data consistency, physics-based consistency constraint loss including conjugateray consistency loss and accumulation-ray consistency loss is designed. Extensive experiments are carried out to verify the performance of our algorithm on the publicly availab.e dataset and clinical experimental dataset. This efficient, accurate, and reliable MAR approach holds great potential in clinics. © 2023 IEEE.

关键词： computed tomography deep unsupervised learning denoising diffusion probabilistic model Metal artifact reduction physics-based consistency constraint

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An Improved AODV Routing Protocol Based on Remaining Power and Fame

An Improved AODV Routing Protocol Based on Remaining Power a...

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International Conference on Electronic computer technology

作者： Daming Feng Yanqin Zhu Provincial Key Laboratory of Computer Information Processing Technology Soochow University Suzhou China Soochow University Suzhou Jiangsu CN

ISBN: (纸本)9781424435623

Almost all proposed routing protocols are based on minimum hops in mobile ad hoc network. But through the research on the real communication of wireless nodes, we find that sometimes the path which has the minimum hops from the source to the destination may not be the best path. Considered the remaining power and the node selfishness, we propose an improved AODV routing protocol, I-AODV in this paper. We use a new term, node status, regard the node status as a function of the remaining power and the fame and regard the node status as the basic condition for choosing the next hop in the new routing protocol.

关键词： Routing protocols Ad hoc networks Monitoring Mobile ad hoc networks lab.ratories computer networks information processing Mobile communication Wireless communication Data communication

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Adaptive Shadows Detection Algorithm Based on Gaussian Mixture Model

Adaptive Shadows Detection Algorithm Based on Gaussian Mixtu...

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International Symposium on information Science and Engineering, ISISE

作者： Yu-jiao XiaHou Sheng-rong Gong Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou China Soochow University Suzhou Jiangsu CN

This paper proposed an adaptive shadows detection algorithm based on Gaussian Mixture Model to improve the performance of video object segmentation. This method takes advantage of luminance weight to model the background of the image and obtains a primary segmentation in CIE Luv color space. In this way, it improves the real-time ability of detection. It also becomes more efficient, comparing with the existing shadow detection algorithms which often need to set the threshold manually or get them through a training process. By using the Gaussian distribution, it is able to realize an adaptive shadow detection. At same time, the authors deal with the noise or the aim points uneven distribution by using horizontal filling and vertical filling. It improves the accuracy of segmentation. The experimental results have shown that this method achieves adaptive shadows detection and has strong robustness, high segmentation accuracy.

关键词： Detection algorithms Clustering algorithms Layout Gaussian distribution Pixel Object segmentation Filling Object detection Streaming media information science

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Ranking based activity trajectory search

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8786卷 170-185页

作者： Chen, Wei Zhao, Lei Jiajie, Xu Zheng, Kai Zhou, Xiaofang School of Computer Science and Technology Soochow University China Jiangsu Provincial Key Laboratory for Computer Information Processing Technology Soochow University China School of ITEE The University of Queensland Brisbane Australia

With the proliferation of the GPS-enabled devices and mobile techniques, there has been a lot of work on trajectory search in the last decade. Previous trajectory search has focused on spatio-temporal features and text descriptions. Different from them, we study a novel problem of searching trajectories with activities and corresponding ranking information. Given a query q, which is attached with a set of activities and a threshold of distance, the results of ranking based activity trajectory search (RTS) are k trajectories such that the given activities are performed with the highest ranking within the threshold of distance. In addition, we also extend the query with an order, i.e., order-sensitive ranking based activity trajectory search (ORTS), which takes both the order of activities in a query q and the order of trajectories into account. It is challenging to answer RTS and ORTS efficiently due to the structural complexity of trajectory data with ranking information. In this paper, a hybrid index AC-tree and its optimized variant RAC-tree are proposed to achieve higher efficiency. Extensive experiments verify the high efficiency and scalab.lity of the proposed algorithms. © Springer International Publishing Switzerland 2014.

关键词： Trajectories

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Character-Level Street View Text Spotting Based on Deep Multisegmentation Network for Smarter Autonomous Driving

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2022年第2期3卷 297-308页

作者： Zhang, Chongsheng Tao, Yuefeng Du, Kai Ding, Weiping Wang, Bin Liu, Ji Wang, Wei Henan Provincial Key Laboratory of Big Data Analysis and Processing Laboratory of the Yellow River Cultural Heritage Henan University Kaifeng475001 China School of Information Science and Technology Nantong University Nantong226019 China School of Electrical Engineering Zhejiang University Hangzhou310058 China Big Data Lab Baidu Inc. Beijing100044 China School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China

Urban scenes are full of street entities with sign boards. Therefore, in autonomous driving, street view text spotting techniques will play a significant role in the precise understanding of surrounding scenes during driving, because texts contained in the images usually provide important clues for accurate image understanding, while it is often ambiguous for existing computer vision algorithms to understand scene images without texts. In this work, we propose a Multi-Segmentation network for character-level scene Text Detection (MSTD). The MSTD introduces a densely connected atrous spatial pyramid pooling module to enlarge the receptive field of the feature extraction layer, so as to localize long as well as large-sized text instances. Moreover, it devises a double segmentation subnetwork to utilize two independent but inherently complementary losses to co-optimize the network and increase the reliability of the confidence scores in predicting the text/nontext areas. With the character instances detected by the MSTD, one can easily perform scene text spotting with classic object recognition networks such as ResNet and DenseNet. We carried out extensive experiments on nine scene text datasets to demonstrate the outstanding performance of the MSTD on character-level and line-level text instance localization and scene text recognition, where the MSTD significantly outperforms the state-of-the-art scene text detection methods and the sequence-to-sequence-learning-based scene text recognizers. © 2020 IEEE.

关键词： Character recognition

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A Policy-Controlled Signature Scheme for end-to-end Secure Communication 12

A Policy-Controlled Signature Scheme for end-to-end Secure C...

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12th International Conference on Advanced Cloud and Big Data, CBD 2024

作者： Yu, Feng Meng, Linghui Xi, Jing Li, Xianxian Lu, Qianhui Zhu, Weidong Guangxi Normal University Key Lab of Education Blockchain and Intelligent Technology GuiLin China University of SouthEast Jiangsu Provincial Key Laboratory of Netwrok and Information Security Nanjing China Guangxi Normal University Guangxi Key Lab of Multi-Source Information Mining and Security GuiLin China Guangxi Collaborative Innovation Center of Multi-source Information Integration and Intelligent Processing Guangxi Normal University GuiLin China

ISBN: (纸本)9798331511074

In the digitalized society, end-to-end security communication is receiving increasing attention. Issues such as ma-licious sender impersonation and over-privilege communication continue to prevail in end-to-end communication. This paper pro-poses a policy-controlled signature scheme aimed at addressing these concerns through identity verification and permission man-agement, thus establishing a secure mode of communication. The scheme designs policy-controlled signatures with partial policy hiding functionality, employing expressive access structures and garbled Bloom Filter (GBF) to protect the sender's attributes. In comparison to related approaches, this scheme provides benefits in terms of signature computation cost, thereby enhancing the resilience and efficiency of the communication system against attacks. © 2024 IEEE.

关键词： Authentication Protocol

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