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2012 IEEE 5th International Conference on Advanced Computational Intelligence, ICACI 2012

作者： Wu, Shuang Fan, Yawen Zheng, Shibao Yang, Hua Institute of Image Communication and Network Engineering Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9781467317436

Object tracking is an important issue in video surveillance. In this paper, we present a tracking framework based on ORB (Oriented FAST and Rotated BRIEF) feature using temporal-spacial constraint. ORB is a fast binary descriptor which needs low computation cost and has similar matching performance with SIFT or SURF. Firstly, ORB keypoints and their descriptors of the object are calculated on two adjacent frames. Afterwards, a best match between these two point sets is obtained through computing Hamming distance. Then, the next location of the object can be deduced from the matched keypoints. In the case of without match, we can still predict the target's location using temporal-spacial constraint. The performance of our tracking system is evaluated on datasets of real surveillance scenes. The experiments results show that the presented approach can track objects accurately and efficiently. © 2012 IEEE.

关键词： Hamming distance

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Adaptive resampling in particle filter based on diversity measures

Adaptive resampling in particle filter based on diversity me...

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International Conference on Computer Science and Education

作者： Yu, Jin-Xia Liu, Wen-Jing Tang, Yong-Li College of Computer Science and Technology Henan Polytechnic University Jiaozuo 454003 China Jiangsu Provincial Key Lab. of Image Processing and Image Communication Nanjing University of Posts and Communication Nanjing 210003 China Department of Computer Science and Technology Tsinghua University Beijing 100084 China

ISBN: (纸本)9781424460052

It is very important to find a criterion when to perform a resampling step. Aimed at this problem, an adaptive resampling algorithm in particle filter based on diversity measures is presented. Based on the analysis and comparison of two diversity measures that are effective sample size (ESS) and population diversity factor(PDF), the resampling algorithm based on ESS is introduced. On the basis of that, PDF is used for adaptively tuning the resampling threshold. At last, with the simulation program using matlab 7.0 to track a single target motion from a fixed visual observation points, the performance of the proposed algorithm is evaluated and its validity is verified. ©2010 IEEE.

关键词： MATLAB

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Automatic ship detection in SAR image based on Multi-scale Faster R-CNN 4

Automatic ship detection in SAR Image based on Multi-scale F...

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2020 4th International Workshop on Advanced Algorithms and Control Engineering, IWAACE 2020

作者： Zhou, Yiqing Cai, Zemin Zhu, Yuting Yan, Jingwen Guangdong Provincial Key Laboratory of Digital Signal and Image Processing Shantou Guangdong515063 China College of Engineering Shantou University Shantou Shantou515063 China

Automatic ship detection of synthetic aperture radar (SAR) images has been widely used in maritime surveillance. SAR images have the characteristics of all-weather, all-day detection. Therefore, many object detection methods ranging from traditional to deep learning techniques have been proposed. However, the objects in large-scale remote sensing images are relatively small, and objects are often appeared at different scales. What's more, the current ship detection methods are insensitive to small-scale vessels. To solve these problems, a novel multi-scale ship detection method based on a Multi-scale Faster R-CNN network in SAR images is proposed in this paper. Firstly, a multi-scale network is used to decompose the SAR images into a pyramid structure and extract the features. Then, the region proposal network (RPN) is performed using the feature map for each layer to get the proposals that contains ship targets. Finally, these proposals are fed to the classification and regression network to obtain the final detection results. Multi-scale Faster R-CNN achieves the mean average precision(mAP) score 0.986 on the dataset of SAR-Ship-Dataset, which indicates that the proposed method has high detection accuracy and low missing rate. © 2020 IOP Publishing Ltd. All rights reserved.

关键词： Synthetic aperture radar

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Privacy and Security in Ubiquitous Integrated Sensing and communication: Threats, Challenges and Future Directions

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IEEE Internet of Things Magazine 2024年第4期7卷 52-58页

作者： Qu, Kaiqian Ye, Jia Li, Xuran Guo, Shuaishuai School of Control Science and Engineering Shandong University China Shandong University Shandong Key Laboratory of Wireless Communication Technologies China School of Electrical Engineering Chongqing University China School of Physics and Electronics Shandong Normal University Shandong Key Laboratory of Medical Physics and Image Processing China

Integrated sensing and communication (ISAC) technology is at the forefront of next-generation communication, enhancing applications from intel-ligent transportation to unmanned aerial vehicle surveillance and healthcare through ubiquitous sensing capability. However, the advent of ISAC brings with it a dual-edged challenge. While it opens up new avenues for application, it also raises significant concerns regarding the privacy of sensitive data and the security of systems in an inherently open environment. To navigate these challenges and unlock ISAC's full potential, this article starts with an analysis of the underlying factors that contribute to privacy and security vulnerabilities. It also identifies the technical obstacles that stand in the way of achieving a secure and private ISAC ecosystem within the confines of conventional network frameworks. As a solution, we introduce a security and privacy-preserving network (SPPN), designed to mitigate these potential threats and tackle the technical challenges through a secure framework for information handling and collaborative efforts among trusted parties, ISAC operators, and users. Central to SPPN's security strategies is an artificial intelligence based system, equipped to detect unauthorized access and coordinate defense mechanisms, including deploying friendly jammers to thwart malicious devices and utilizing reconfigurable intelligent surfaces (RISs) to bolster the network's defense mechanisms against potential attacks. Through detailed analysis and case studies, this article demonstrates the effectiveness of the SPPN framework, which not only strengthens the network's defenses but also significantly improves its sensing and communication capabilities. © 2018 IEEE.

关键词： Sensitive data

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Attention-based end-to-end models for small-footprint keyword spotting 19

Attention-based end-to-end models for small-footprint keywor...

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19th Annual Conference of the International Speech communication, INTERSPEECH 2018

作者： Shan, Changhao Zhang, Junbo Wang, Yujun Xie, Lei Shaanxi Provincial Key Laboratory of Speech and Image Information Processing School of Computer Science Northwestern Polytechnical University Xi'an China Xiaomi Inc. Beijing China

In this paper, we propose an attention-based end-to-end neural approach for small-footprint keyword spotting (KWS), which aims to simplify the pipelines of building a production-quality KWS system. Our model consists of an encoder and an attention mechanism. Using RNNs, the encoder transforms the input signal into a high level representation. Then the attention mechanism weights the encoder features and generates a fixed-length vector. Finally, by linear transformation and softmax function, the vector becomes a score used for keyword detection. We also evaluate the performance of different encoder architectures, including LSTM, GRU and CRNN. Experiments on wake-up data show that our approach outperforms the recent Deep KWS approach [9] by a large margin and the best performance is achieved by CRNN. To be more specific, with ∼84K parameters, our attention-based model achieves 1.02% false rejection rate (FRR) at 1.0 false alarm (FA) per hour. © 2018 International Speech communication Association. All rights reserved.

关键词： Linear transformations

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Theoretical design of single-molecule NOR and XNOR logic gates by using transition metal dibenzotetraazaannulenes

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Chinese Physics B 2020年第6期29卷 411-418页

作者： Zi-Qun Wang Fei Tang Mi-Mi Dong Ming-Lang Wang Gui-Chao Hu Jian-Cai Leng Chuan-Kui Wang Guang-Ping Zhang Shandong Key Laboratory of Medical Physics and Image Processing&Shandong Provincial Engineering and Technical Center of Light Manipulations School of Physics and ElectronicsShandong Normal UniversityJinan 250358China Department of Physics School of Electronic and Information EngineeringQilu University of Technology (Shandong Academy of Sciences)Jinan 250353China

The idea of replacing traditional silicon-based electronic components with the ones assembled by organic molecules to further scale down the electric circuits has been attracting extensive research *** the molecularly assembled components,the design of molecular logic gates with simple structure and high Boolean computing speed remains a great ***,by using the state-of-the-art nonequilibrium Green’s function theory in conjugation with first-principles method,the spin transport properties of single-molecule junctions comprised of two serially connected transition metal dibenzotetraaza[14]annulenes(TM(DBTAA),TM=Fe,Co)sandwiched between two single-walled carbon nanotube electrodes are theoretically *** numerical results show a close dependence of the spin-resolved current-voltage characteristics on spin configurations between the left and right molecular kernels and the kind of TM atom in TM(DBTAA)*** taking advantage of spin degree of freedom of electrons,NOR or XNOR Boolean logic gates can be realized in Fe(DBTAA)and Co(DBTAA)junctions depending on the definitions of input and output *** work proposes a new kind of molecular logic gates and hence is helpful for further miniaturization of the electric circuits.

关键词： single-molecule junction molecular logic gate spin transport nonequilibrium Green’s function method

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Intrinsic spectral analysis based on temporal context features for query-by-example spoken term detection 15

Intrinsic spectral analysis based on temporal context featur...

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15th Annual Conference of the International Speech communication Association: Celebrating the Diversity of Spoken Languages, INTERSPEECH 2014

作者： Yang, Peng Leung, Cheung-Chi Xie, Lei Ma, Bin Li, Haizhou Shaanxi Provincial Key Laboratory of Speech and Image Information Processing School of Computer Science Northwestern Polytechnical University Xi'an China Institute for Infocomm Research ASTAR Singapore

We investigate the use of intrinsic spectral analysis (ISA) for query-by-example spoken term detection (QbE-STD). In the task, spoken queries and test utterances in an audio archive are converted to ISA features, and dynamic time warping is applied to match the feature sequence in each query with those in test utterances. Motivated by manifold learning, ISA has been pro- posed to recover from untranscribed utterances a set of nonlin- ear basis functions for the speech manifold, and shown with improved phonetic separability and inherent speaker indepen- dence. Due to the coarticulation phenomenon in speech, we propose to use temporal context information to obtain the ISA features. Gaussian posteriorgram, as an efficient acoustic rep- resentation usually used in QbE-STD, is considered a baseline feature. Experimental results on the TIMIT speech corpus show that the ISA features can provide a relative 13.5% improvement in mean average precision over the baseline features, when the temporal context information is used. Copyright © 2014 ISCA.

关键词： Spectrum analysis

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A novel computational approach to predict activity of nuclear export signals

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Journal of Computational and Theoretical Nanoscience 2015年第12期12卷 6016-6019页

作者： Chen, Zhihua Zhang, Pan Wu, Tingfang Shi, Xiaolong Wang, Xun Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology WuhanHubei430074 China College of Computer and Communication Engineering China University of Petroleum QingdaoShandong266580 China

A nuclear export signal (NES) is a sequence of amino acids, which is a protein localization signal, and contributes to regulate localization of cellular proteins. In recent peering works, activity of NESs were introduced in computational methods, which perform significantly well in identifying unknown NESs even from huge datasets, but suffer from a shortage that only a small number of NESs are associated with experimental verified active scores. In this work, we propose a novel computational method to predict active score of NESs. Specifically, we firstly abstract relevant features to NES activity, and then construct a mathematical model based on principal component analysis (PCA) to find each feature's contribution to activity. In this way, a method to calculate active score of unknown NESs is achieved. In data experiments, it is obtained that our method can achieve accuracy rate 80%. The activity of an unknown NES candidate can give us a preliminary understanding of it, and can be used to identify positive NESs from the negative ones. To the best acknowledge of the authors, this is the first time computational method is proposed to predict NESs' activity. Copyright © 2015 American Scientific Publishers All rights reserved.

关键词： Computational methods

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Broadcast news story segmentation using probabilistic latent semantic analysis and laplacian eigenmaps

Broadcast news story segmentation using probabilistic latent...

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Asia-Pacific Signal and Information processing Association Annual Summit and Conference 2011, APSIPA ASC 2011

作者： Lu, Mimi Zheng, Lilei Leung, Cheung-Chi Xie, Lei Ma, Bin Li, Haizhou Shaanxi Provincial Key Laboratory of Speech and Image Information Processing School of Computer Science Northwestern Polytechnical University Xi'an China Institute for Infocomm Research A STAR Singapore

This paper proposes to integrate probabilistic latent semantic analysis (PLSA) and Laplacian Eigenmaps (LE) for broadcast news story segmentation. PLSA can address synonymy and polysemy problems by exploring underlying semantic relations beneath the actual occurrences of words. LE can provide a data transformation with the advantage of preserving the original temporal structure of sentence cohesive *** adopt PLSA statistics to replace term frequency as the representation of sentences and measure their connective strength. LE analysis is then performed on the connective strength matrix so that the sentence relations becomes geometrically evident for discriminating different stories. A dynamic programming (DP) algorithm is used for story boundary identification. Experiments show that the proposed method achieves superior story segmentation performances with the highest F1-measure of 0:7536 on TDT2 Mandarin BN corpus.

关键词： Semantics

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An adaptive multi-scale tracking method based on Kernelized Correlation Filter 14th

An adaptive multi-scale tracking method based on Kernelized ...

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14th International Forum of Digital TV and Wireless Multimedia communication, IFTC 2017

作者： Xu, Qiling Yang, Hua Institue of Image Communication and Network Engineering Shanghai Jiao Tong University Shanghai China Shanghai Key Laboratory of Digital Media Processing and Transmission Shanghai China

ISBN: (纸本)9789811081071

Visual tracking is a fundamental computer vision task with a wide range of applications. Kernelized Correlation Filter (KCF) is an excellent algorithm with high tracking speed. However, the target tracking scale in the KCF algorithm is a fixed value which might cause tracking failure or target drifting problem when the target scale changes significantly. In this paper, we present an adaptive multi-scale tracking algorithm based on the KCF algorithm by estimating the scale of the target. Our method builds upon the correlation filter with a Gaussian kernel and reasonable prediction of the target size. In order to verify the effectiveness of the proposed algorithm, 9 sets of complex video sequences of a commonly used tracking benchmark were selected and the results were compared with other tracking methods (KCF, CSK, CT, TLD, Struck, CNN-SVM and MDNet). The results show that the proposed method has high accuracy. The method in this paper has strong robustness in the complex scenes with challenges of scale variation, illumination variation, occlusion, in-plane rotation, out-of plane rotation and deformation. © 2018, Springer Nature Singapore Pte Ltd.

关键词： Target tracking

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