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IEEE International Conference on Systems, Man and Cybernetics

作者： Zhengwei Ren Xiaoshuang Chen Jinshan Tang Lina Wang Yan Tong Shiwei Xu School of Computer Science and Technology Wuhan University of Science and Technology and Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China College of Health and Human Services George Mason University Fairfax VA USA School of Cyber Science and Engineering Wuhan University Wuhan China Huazhong Agricultural University Wuhan China

ISBN: (纸本)9781665442084

It is straightforward to encrypt the outsourced data to protect its confidentiality using symmetric cryptography in cloud storage. How to control and restrict the use of the encryption key in data users’ devices becomes one of the critical issues. In most of existing time-based and policy-based schemes, the key cannot be stored locally in data users’ devices, making the traffic cost linear with the data access times as the key should be retrieved in each data access. In this paper, we propose a times-based scheme with Intel SGX to restrict the times the key can be used in the data user’s device to restrict the times of data access. The basic idea is to compare the current used times with the specified maximal times to determine whether the key can be used or not. To this end, we use a monotonic counter to count the times the key has been used. When the use condition is not satisfied, we destroy the key securely and generate public proof so that (i) the encrypted data cannot be accessed anymore, i.e., the data is deleted assuredly, (ii) the deletion can be verified. In addition, a hash-based integrity check approach is utilized to detect and prevent replay attacks. The experimental results on the implemented prototype show our scheme is feasible in practice.

关键词： Cloud computing Costs Conferences Prototypes Encryption Cybernetics

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Effect analysis of antenna translation vibration on GEO SARimage

Effect analysis of antenna translation vibration on GEO SARi...

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IET International Radar Conference 2018, IRC 2018

作者： Zhang, Tianyi Lv, Zheng Yin, Wei Ke, Meng Li, Gen Ding, Zegang Radar Research Lab. School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Institute of Spacecraft System Engineering Beijing China Shijiazhuang China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology Beijing China

Due to the high orbital altitude, the large-area antenna and solar array will be utilised in geosynchronous synthetic aperture radar (GEO SAR) to meet the requirement of high transmitting power. However, the large-area antenna and solar array can easily cause antenna translation vibration (ATV) and further result in paired echo, which will seriously affect the GEO SAR image quality. Existing effect analyses of antenna vibration for low-earth-orbit SAR (LEO SAR) based on the linear trajectory and the corresponding second-order Doppler spectrum cannot be applied in GEO SAR because of its extremely long synthetic aperture time (SAT), curved trajectory, and corresponding high-order Doppler spectrum. To analyse the effects of ATV on GEO SAR image, the ideal echo signal model and the corresponding point spread function (PSF) of GEO SAR are first established and deducted, respectively. Then, the echo signal model and PSF affected by ATV are obtained. Based on the affected PSF, the effects of the ATV on GEO SAR image are analysed in detail, and the basis for subsequent ATV suppression is also obtained. Computer simulations validate the correctness of the analyses shown here. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Synthetic aperture radar

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A Novel Method based on Character Segmentation for Slant Chinese Screen-render Text Detection and Recognition

A Novel Method based on Character Segmentation for Slant Chi...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Tianlun Zheng Xiaofeng Wang Xin Yuan Shiqin Wang School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan China

ISBN: (数字)9781728151694

ISBN: (纸本)9781728151700

Screen rendering text has broad application prospects in the fields of medical records, dictionary screen capture, and screen-assisted reading. However, Chinese screen rendering text always has the challenges of small font size and low resolution. Obtaining a screen-rendered text image in a natural scene will have a certain tilt angle. These all pose great challenges for screen text recognition. This paper proposes a method based on character segmentation. In order to correct the tilt of the text image, a lightweight image text correction method is proposed. In order to obtain better character segmentation accuracy in extreme environments, a Gaussian extremum removal module is designed. Drawing on HCCR-GoogLeNet, a simple and efficient network architecture is designed for character recognition. Finally, this paper will slant text correction, horizontal text line detection, character segmentation, and character recognition to construct a complete network architecture to be applied to the screen rendering text recognition process scheme in natural scenes. The character recognition model was evaluated on ICDAR2013 and the homemade screen rendering dataset, and both achieved good results.

关键词： Image segmentation Text recognition Network architecture Rendering (computer graphics) Optical imaging Character recognition Optical character recognition software

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Spaceborne Large-Squint Terrain-Matching Synthetic Aperture Radar: Concept and technology

Spaceborne Large-Squint Terrain-Matching Synthetic Aperture ...

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Asian and Pacific Conference on Synthetic Aperture Radar (APSAR)

作者： Yan Wang Zhe Li Zegang Ding Tao Zeng Radar Research Lab Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China

ISBN: (数字)9781728129129

ISBN: (纸本)9781728129136

This paper discusses a new spaceborne large-squint terrain-matching synthetic aperture radar (LSTM-SAR) to effectively image the terrains that do not spread along satellite orbit. Different from the traditional spaceborne SAR, the swath of the LSTM-SAR spreads along the target terrain, instead of the satellite orbit, to perform terrain-matched imaging with both high resolution and short data acquisition period. Aiming at giving a sketch of how the LSTM-SAR works, the paper focuses on discussing the following three main aspects: the data acquisition geometry, azimuth sampling manner and raw data focusing algorithm. Specifically, an optimum squint geometry is firstly suggested for two dimensional swath optimization; then two non-uniform azimuth sampling methods are discussed to avoid data loss induced by transmission blockage; lastly, a wide nonlinear chirp scaling based algorithm is discussed to focus the spatially variant spaceborne LSTM-SAR echo. The presented approach is validated via the computer simulations.

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A bilayer segmentation-recombination network for accurate segmentation of overlapping C. elegans

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Applied Soft Computing 2025年 180卷

作者： Mengqian Ding Jun Liu Yang Luo Jinshan Tang School of Computer Science and Technology Wuhan University of Science and Technology Wuhan Hubei 430065 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan 430065 China School of Electronic Information Wuhan University of Science and Technology Wuhan Hubei 430065 China Health Informatics Department of Health Administration and Policy College of Public Health George Mason University Fairfax VA 22312 USA

Caenorhabditis elegans ( C. elegans ) is an excellent model organism because of its short lifespan and high degree of homology with human genes, and it has been widely used in a variety of human health and disease models. However, the segmentation of C. elegans remains challenging due to the following reasons: 1) the activity trajectory of C. elegans is uncontrollable, and multiple nematodes often overlap, resulting in blurred boundaries of C. elegans . This makes it impossible to clearly study the life trajectory of a certain nematode; and 2) in the microscope images of overlapping C. elegans , the translucent tissues at the edges obscure each other, leading to inaccurate boundary segmentation. To solve these problems, a Bilayer Segmentation-Recombination Network (BR-Net) for the segmentation of C. elegans instances is proposed. The network consists of three parts: A Coarse Mask Segmentation Module (CMSM), a Bilayer Segmentation Module (BSM), and a Semantic Consistency Recombination Module (SCRM). The CMSM is used to extract the coarse mask, and we introduce a United Attention Module (UAM) in CMSM to make CMSM better aware of nematode instances. The Bilayer Segmentation Module (BSM) segments the aggregated C. elegans into overlapping and non-overlapping regions. This is followed by integration by the SCRM, where semantic consistency regularization is introduced to segment nematode instances more accurately. Finally, the effectiveness of the method is verified on the C. elegans dataset. The experimental results show that BR-Net exhibits good competitiveness and outperforms other recently proposed segmentation methods in processing C. elegans occlusion images.

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Novel acceleration compensation method for highly squint mode SAR with curve trajectory

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The Journal of Engineering 2019年第20期2019卷 6527-6532页

作者： Zhichao Zhou Zegang Ding Tao Zeng Gen Li Linghao Li School of Information and Electronics Beijing Institute Technology Beijing People's Republic of China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing People's Republic of China

Due to the influence of air currents and the control of the platform's own power system, acceleration is often present in the motion platform equipped with synthetic aperture radar (SAR) system, which causes the actual trajectory of the platform to be curved. When the acceleration is large or the azimuth accumulation time is long, a large envelope error or phase error will be caused. This problem will be more obvious in highly squint mode SAR. On the other hand, the acceleration may also cause the situation where the absolute value of the Doppler frequency rate is extremely small, resulting in the azimuthal time-bandwidth product that is too small to satisfy the requirements of the stationary phase principle. To solve the above problems, a novel acceleration compensation method based on inertial navigation information is proposed in this article. By integrating the acceleration and velocity information provided by the inertial navigation system, the position information of maneuvering platform is obtained. Then the actual trajectory of the platform is constructed. On this basis, the envelope and phase errors caused by the acceleration are estimated. The results of real data processing verify the correctness of the analysis and the effectiveness of the proposed method.

关键词： inertial navigation radar imaging synthetic aperture radar compensation real data processing position information acceleration information velocity information power system control phase errors maneuvering platform inertial navigation system inertial navigation information stationary phase principle azimuthal time-bandwidth product Doppler frequency rate envelope error azimuth accumulation time synthetic aperture radar system motion platform air currents curve trajectory highly squint mode SAR novel acceleration compensation method

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Radar HRRP target recognition based on stacked denosing sparse autoencoder

Radar HRRP target recognition based on stacked denosing spar...

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IET International Radar Conference 2018, IRC 2018

作者： Tai, Guangxing Wang, Yanhua Li, Yang Hong, Wei Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology Beijing100081 China Beijing Racobit Electronic Information Technology Co. Ltd. Beijing100081 China

An end-to-end radar high-resolution range profile recognition method is proposed based on stacked denosing sparse autoencoder which stacks several denosing sparse autoencoders and uses softmax as the classifier. The training process consists of two steps. The first is layer-by-layer pre-training and the second is fine tuning using the pre-training results for initialisations. The two-step training process makes this model converge faster and more likely to converge to the global optimal point than directly training the joint network. Experimental result shows that the proposed method achieves higher recognition accuracy than state-of-art methods. © This is an open access article published by the IET under the Creative Commons Attribution License (http://***/licenses/by/3.0/)

关键词： Learning systems

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Social Emergency Event Judgement based on BiLSTM-CRF 19

Social Emergency Event Judgement based on BiLSTM-CRF

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19th Chinese National Conference on Computational Linguistic, CCL 2020

作者： Hu, Huijun Wang, Cong Dai, Jianhua Liu, Maofu School of Computer Science and Technology Wuhan University of Science and Technology Wuhan430065 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan430065 China Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing Hunan Normal University Changsha410081 China

In recent years, classification and rating of social emergency event have attracted more and more attentions in emergency management. However, most of the current studies adopt the rule-based methods to identify the evidences for event judgement, and have troubles in event judgement due to the complexity of social emergency event composition and the flexibility of language description. Inspired by the idea of event extraction, this paper has proposed the event judgement method via BiLSTM (Bidirectional Long-Short Term Memory) and CRF (Conditional Radom Fields) based on event classification and evidence extraction. The social emergency event classification is carried out firstly, and then the event evidences are extracted based on event type. In the end, the rating of social emergency event is judged with the attention mechanism and the combination of event type and evidence. Experimental results show that the proposed method is more robust than rule-based ones, and effective in the social emergency event judgement. © 2020 China National Conference on Computational Linguistics Published under Creative Commons Attribution 4.0 International License

关键词： Extraction

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An improved RUDP for data transmission in embedded real-time system

An improved RUDP for data transmission in embedded real-time...

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2019 IEEE International Conference on Signal, information and Data processing, ICSIDP 2019

作者： Chen, Yingying Hu, Shanqing Li, Xingming Wang, Ce Chen, Zhe Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing100081 China Beijing Racobit Electronic Information Technology Co.Ltd Beijing100081 China Academy of Broadcasting Science Internet Technology Institute Beijing100081 China

ISBN: (纸本)9781728123455

At present, the Ethernet has been widely used for data transmission in embedded real-time systems, including TCP (Transmission Control Protocol) and UDP (User Datagram Protocol). However, as embedded real-time systems continue to increase the requirements of transmission speed and reliability, TCP and UDP have not been able to meet the requirements. TCP is a stream-based, connection-oriented communication protocol, so the reliability of TCP is good. But its design is complicated, it occupies a lot of system resources, and the transmission speed of TCP is low. In contrast, UDP is non-connection-oriented protocol, so it is unreliable communication protocol. Both of them limit the Ethernet applying in embedded real-time systems. In order to meet the requirements of real-time, reliability and algorithm simplicity of embedded systems, this paper proposed an improved Reliable User Datagram Protocol (RUDP), which offers a solution to satisfy these requirements. It is valid on the real demonstration that the proposed method can offer a higher speed than TCP without package loss. © 2019 IEEE.

关键词： Transmission control protocol

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Deep forest for radar HRRP recognition

Deep forest for radar HRRP recognition

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IET International Radar Conference 2018, IRC 2018

作者： Wang, Yanhua Bi, Xuejie Chen, Wei Li, Yang Chen, Qiao Long, Teng Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China Beijing Racobit Radar Technology Research Institute Co. Ltd. Beijing China

High-resolution range profile (HRRP) has received intensive attention in the radar automatic target recognition filed. Here, deep forest is applied to the recognition of HRRP. The deep forest is a deep learning method, which is a cascade of ensemble learners. In each layer, there are various ensemble learners. The input of each layer is the combination of the previous layer output and the original input data. The number of cascade levels can be adaptively determined such that the model complexity can be automatically set. Experiments based on measured data show that deep forest is feasible and achieves highly competitive performance for HRRP recognition. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Deep learning

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