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International Conference on information and Computing Science, ICIC

作者： Jun Liu Jianzhong Qiao Shukuan Lin Qian Li College of Information Science and Engineering Northeastern University Shenyang China Key Laboratory of Software System Application and Development Generic Technology Science and Technology Bureau Shenyang China

This paper presents a systematic way of making effort estimation for service oriented software. By outlining major governance processes identified from service oriented best practices, an effort estimation model based on Bayesian net is introduced. Effort estimation method and project application results based on this model have been discussed thereafter.

关键词： Bayesian methods Object oriented modeling application software Service oriented architecture Resource management Monitoring system testing Solid modeling Software systems Best practices

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Wave model based enhancement of SAR ocean images

Wave model based enhancement of SAR ocean images

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6th International Conference on Radar, RADAR 2011

作者： Zhang, Wen-Yi Li, Fang-Fang Hu, Dong-Hui Ding, Chi-Biao Zhong, Li-Hua Institute of Electronics Chinese Academy of Sciences Beijing 100190 China Graduate University Chinese Academy of Sciences Beijing 100039 China Key Laboratory of Spatial Information Processing and Application System Technology No. 19 North 4th Ring Road West Haidian District Beijing 100190 China

Enhanced SAR ocean images with dominant wave-like signatures might promote oceanographic applications. Therefore we develop a wave model based processor for wave features enhancement. Algorithm analysis and experiment... 详细信息

ISBN: (纸本)9781424484416

关键词： Synthetic aperture radar

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Radial Velocity Ambiguity Resolution Method in Azimuth Multichannel HRWS SAR

Radial Velocity Ambiguity Resolution Method in Azimuth Multi...

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IEEE International Conference on Radar

作者： Junying Yang Xiaolan Qiu Mingyang Shang Lihua Zhong Yini Lv Chibiao Ding Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Aerospace Information Research Institute Chinese Academy of Sciences Beijing China National Key Laboratory of Microwave Imaging Technology Aerospace Information Research Institute Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665468893

For moving targets in synthetic aperture radar (SAR) images, the obvious features are defocusing and dislocation. To estimate motion parameters accurately is a premise for the precise imaging of moving targets. However, when the radial velocity of the target exceeds the maximum detectable unambiguous velocity, the estimated value by the existing methods is no longer the real value. A radial velocity ambiguity resolution method based on Imaging Space-Time Adaptive Processing (ISTAP) is proposed in this paper. The proposed method has no search or iterative process and is suitable for the azimuth multichannel SAR with low pulse repetition frequency (PRF). Finally, the simulated data from an x-band azimuth six-channel SAR system verify the feasibility of the proposed method.

关键词： Baseband Image resolution Azimuth Energy resolution Imaging Estimation Radar imaging

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Robust moving object segmentation in the compressed domain for H.264/AVC video stream

Robust moving object segmentation in the compressed domain f...

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25th PCS: Picture Coding Symposium 2006, PCS2006

作者： Yang, Gaobo Yu, Shengfa Zhang, Zhaoyang Network and Information Security Lab School of Computer and Communication Hunan University Changsha Hunan 410082 China School of Electronic Science and Engineering National University of Defense Technology Changsha Hunan 410073 China Key Laboratory of Advanced Displays and System Application Shanghai University Ministry of Education Shanghai 200072 China

ISBN: (纸本)300018726X

Moving object segmentation in the compressed domain plays an important role in many real-time applications, e.g. video indexing, video surveillance, etc. H.264/AVC is the up-to-date video coding standard, which employs several new coding tools and provides a different video format. In this paper, a robust spatio-temporal segmentation approach to extract moving objects in the compressed domain for H.264 video stream is proposed. Coarse moving objects are firstly extracted from the motion vector field through the MRF classification process. Spatial segmentation is based on the HT coefficient, which is used to refine the object boundary of temporal segmentation results. Fusion of spatio-temporal segmentation is based on region projection based labeling technique. Further edge refinement is performed to smooth the object boundaries. The performance of the proposed approach is illustrated by simulation carried on several test sequences. Experimental results show that the proposed approach can provide the visually similar results as by using spatial domain process with much less computational complexity.

关键词： Image segmentation

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1.8 W, high efficiency, pump-enhanced, narrow linewidth optical parametric oscillator at 3.8 μm

1.8 W, high efficiency, pump-enhanced, narrow linewidth opti...

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作者： Zhao, Gang Tan, Wei Liu, Gaoyou Li, Chen Hu, Qiongyu Guo, Quanxin Zhao, Zhigang Liu, Zhaojun School of Information Science and Engineering Shandong University Qingdao266237 China Key Laboratory of Time and Frequency Primary Standards National Time Service Center Chinese Academy of Sciences Xi'an710600 China Shandong Provincial Key Laboratory of Laser Technology and Application Qingdao266237 China Key Laboratory of Laser & Infrared System Shandong University Ministry of Education Qingdao266237 China Center for Optics Research and Engineering Shandong University Qingdao266237 China

A high efficiency, continuous-wave, narrow linewidth, pump-enhanced optical parametric oscillator (OPO) at 3.8 μm was demonstrated, which was pumped by a 1064 nm fiber laser with a linewidth of 18 kHz. The low frequency modulation locking technique was employed to stabilize the output power. The wavelengths of signal and idler were 1475.5 nm and 3819.9 nm at 25 °C, respectively. The pump-enhanced structure was applied, leading to a maximum quantum efficiency of over 60% with pump power of 3W. The maximum output power of idler light is 1.8 W with a linewidth of 363 kHz. The excellent tuning performance of the OPO was also demonstrated. In order to avoid mode-splitting and decrease of pump enhancing factor due to feedback light in the cavity, the crystal was placed obliquely to the pump beam and the maximum output power was increased by 19%. At the maximum output power of idler light, the M2 factors in the x and y directions were 1.30 and 1.33, respectively. © 2023 Optica Publishing Group.

关键词： Optical parametric oscillators

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Large Language Models are Good Attackers: Efficient and Stealthy Textual Backdoor Attacks

arXiv

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arXiv 2024年

作者： Li, Ziqiang Zeng, Yueqi Xia, Pengfei Liu, Lei Fu, Zhangjie Li, Bin Nanjing University of Information Science and Technology China Big Data and Decision Lab University of Science and Technology of China China CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System China

With the burgeoning advancements in the field of natural language processing (NLP), the demand for training data has increased significantly. To save costs, it has become common for users and businesses to outsource the labor-intensive task of data collection to third-party entities. Unfortunately, recent research has unveiled the inherent risk associated with this practice, particularly in exposing NLP systems to potential backdoor attacks. Specifically, these attacks enable malicious control over the behavior of a trained model by poisoning a small portion of the training data. Unlike backdoor attacks in computer vision, textual backdoor attacks impose stringent requirements for attack stealthiness. However, existing attack methods meet significant trade-off between effectiveness and stealthiness, largely due to the high information entropy inherent in textual data. In this paper, we introduce the Efficient and Stealthy Textual backdoor attack method, EST-Bad, leveraging Large Language Models (LLMs). Our EST-Bad encompasses three core strategies: optimizing the inherent flaw of models as the trigger, stealthily injecting triggers with LLMs, and meticulously selecting the most impactful samples for backdoor injection. Through the integration of these techniques, EST-Bad demonstrates an efficient achievement of competitive attack performance while maintaining superior stealthiness compared to prior methods across various text classifier datasets. © 2024, CC BY.

关键词： Deep neural networks

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Target Amplitude Characteristic Analysis With Neighborhood information Using C-band Circular SAR Data

Target Amplitude Characteristic Analysis With Neighborhood I...

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IEEE International Conference on Radar

作者： Xiaoyang Yue Fei Teng Yun Lin Wen Hong Key Laboratory of Spatial Information Processing and Application System Technology Areospace Information Research Institute Chinese Academy of Sciences Beijing China School of Electronic Information Engineering North China University of Technology Beijing China

ISBN: (纸本)9781665468893

The circular synthetic aperture radar (SAR) can observe the experimental scene from all angles. The backscatter intensity of the target in the scene can be obtained. Different targets in the imaging scene show different amplitude characteristics. For example, significant targets such as buildings and oil tanks show strong response characteristics at certain angles, and secondly, weak response characteristics for targets is shown such as grass and ground. In this article, the omnidirectional scattering intensity data of the target obtained from the radar is used to analyze the amplitude characteristics, and the model is established for different targets to obtain the final result. The fuzzy C-means (FCM) model combined with neighborhood information is used to analyze the target amplitude characteristics. The amplitude characteristics of the target are divided into two categories: strong response and weak response for analysis. The initial two types of cluster centers are set for iteration and finally the target amplitude characteristic reference values at different angles are obtained. C-band circular SAR data is used to validate our method. As a result, the amplitude characteristics of the whole scene using membership degree can be described.

关键词： Analytical models C-band Buildings Scattering Imaging Fuel storage Radar scattering

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Nonparametric statistics inspired similarity measure for accuracy in collaborative filtering

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Journal of Computational information systems 2013年第20期9卷 8397-8406页

作者： Liu, Shichen Xiong, Yan Liu, Qingwen Qi, Xiang Department of Computer Science and Technology University of Science and Technology of China Hefei 230027 China Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing 100190 China

Similarity computation is especially significant in collaborative filtering algorithms. In the existed literatures or large recommender systems, researchers generally use cosine similarity or Pearson correlation coefficient to compute the similarities. However, on one hand, both two measures are more applicable in linear space while the ratings cannot linearly reflect users' interest intensity. On the other hand, different systems have different rating restricts, so it's unreasonable to treat varied systems with the same computation method. In this work, inspired by nonparametric statistics, a sound memory-based method with a novel similarity measure is proposed to eliminate the affection of rating distributions and system diversities on similarity computation. Experiments based on Jester are set to evaluate the performance of the approach. And the highly competitive results show that our approach is able to significantly improve the recommendation quality. © 2013 Binary information Press.

关键词： Collaborative filtering

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Prediction of ENSO using multivariable deep learning

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Atmospheric and Oceanic Science Letters 2023年第4期16卷 51-56页

作者： Yue Chen Xiaomeng Huang Jing-Jia Luo Yanluan Lin Jonathon S.Wright Youyu Lu Xingrong Chen Hua Jiang Pengfei Lin Ministry of Education Key Laboratory for Earth System Modeling and Department for Earth System Science Tsinghua UniversityBeijingChina Institute for Climate and Application Research(ICAR)/CICFEM/KLME/ILCEC Nanjing University of Information Science and TechnologyNanjingChina Ocean and Ecosystem Sciences Division Fisheries and Oceans CanadaBedford Institute of OceanographyDartmouthNova ScotiaCanada National Marine Environmental Forecasting Center State Oceanic AdministrationBeijingChina State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina

本文基于残差神经网络和观测数据构建了一套深度学习多因子预报测模型,以改进厄尔尼诺-南方涛动(ENSO)的预报.该模型基于最大信息系数进行因子时空特征提取,并根据泰勒图的评估标准可自动确定关键预报因子进行预报.该模型在超前8个月以... 详细信息

本文基于残差神经网络和观测数据构建了一套深度学习多因子预报测模型,以改进厄尔尼诺-南方涛动(ENSO)的预报.该模型基于最大信息系数进行因子时空特征提取,并根据泰勒图的评估标准可自动确定关键预报因子进行预报.该模型在超前8个月以内的预报性能要优于当前传统的业务预报模式.2011–2018年间,该模型的预报性能优于多模式集成预报的结果.在超前6个月预报时效上,模型预报相关性可达0.82,标准化后的均方根误差仅为0.58°C,多模式集成预报的相关性和标准化后的均方根误差分别为0.70和0.73°C.该模型春季预报障碍问题有所缓解,并且自动选取的关键预报因子可用于解释热带和副热带热动力过程对于ENSO变化的影响.

关键词： ENSO预报深度学习春季预报障碍多维时空预报因子

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Model selection for high resolution InSAR coherence statistics over urban areas and its application in building detection

Model selection for high resolution InSAR coherence statisti...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Yue Zhang Xian Sun Wenhui Diao Chenyuan Wang Guangluan Xu Hongqi Wang Institute of Electronic Chinese Academy of Sciences Beijing China Key Laboratory of Spatial Information Processing and Application System Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781509033331

The interferometric coherence map is derived from the cross-correlation of two registered synthetic aperture radar (SAR) images. It can give additional information complementary to the intensity image, or act as an independent information source in many applications. Compared to the plenty of work on SAR intensity statistics, there are quite fewer researches on the statistical characters of interferometric SAR (InSAR) coherence. And to our knowledge, all of the existing work that related to InSAR coherence statistics, models the coherence with Gaussian distribution with no discrimination on data resolutions or scene types. Our main contribution is the investigation on the accuracies of several typical models for high resolution coherence statistics over urban areas. We select three typical land classes including trees, buildings, and shadow, as the representatives of urban areas. And different models including Gaussian, Weibull, Rayleigh, Nakagami and Beta are evaluated. Experiment results on TanDEM-X data illustrate that the Beta model reveals a better performance than other distributions. Finally, the Beta model is used in the detection of buildings.

关键词： Coherence Buildings Synthetic aperture radar Urban areas Probability density function Data models Nakagami distribution

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