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Adaptive Locality Preserving Regression

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arXiv 2019年

作者： Wen, Jie Zhong, Zuofeng Zhang, Zheng Fei, Lunke Lai, Zhihui Chen, Runze School of Computer Science and Technology Guangdong University of Technology GuangzhouGuangdong510006 China Institute of Textiles and Clothing Hong Kong Polytechnic University Hong Kong School of Information Technology & Electrical Engineering University of Queensland BrisbaneQLD4072 Australia College of Computer Science and Software Engineering Shenzhen University ShenzhenGuangdong518055 China School of Computer Science and Technology Harbin Institute of Technology Shenzhen Shenzhen518055 China

This paper proposes a novel discriminative regression method, called adaptive locality preserving regression (ALPR) for classification. In particular, ALPR aims to learn a more flexible and discriminative projection that not only preserves the intrinsic structure of data, but also possesses the properties of feature selection and interpretability. To this end, we introduce a target learning technique to adaptively learn a more discriminative and flexible target matrix rather than the pre-defined strict zero-one label matrix for regression. Then a locality preserving constraint regularized by the adaptive learned weights is further introduced to guide the projection learning, which is beneficial to learn a more discriminative projection and avoid overfitting. Moreover, we replace the conventional ‘Frobenius norm’ with the special l2,1 norm to constrain the projection, which enables the method to adaptively select the most important features from the original high-dimensional data for feature extraction. In this way, the negative influence of the redundant features and noises residing in the original data can be greatly eliminated. Besides, the proposed method has good interpretability for features owning to the row-sparsity property of the l2,1 norm. Extensive experiments conducted on the synthetic database with manifold structure and many real-world databases prove the effectiveness of the proposed method. Copyright © 2019, The Authors. All rights reserved.

关键词： Regression analysis

Design and Simulation of 3.9 GHz Microstrip Parallel Coupled Line Band Pass Filter

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Design and Simulation of 3.9 GHz Microstrip Parallel Coupled...

International Conference on Wavelet Active Media technology and information Processing (ICWAMTIP)

作者： A. H. Sani C. Jianwen M. T. Khan S. B. Yussif S. Nahar K. E. Ewald C. C. Ukwuoma School of Information and Communication Engineering University of Electronics Science and Technology of China (UESTC) Chengdu P.R China School of Electronics Science and Engineering University of Electronics Science and Technology of China (UESTC) Chengdu P.R China School of Computer Science and Engineering University of Electronics Science and Technology of China (UESTC) Chengdu P.R China School of Information and Software Engineering University of Electronics Science and Technology of China (UESTC) Chengdu P.R China

ISBN: (数字)9781728142425

ISBN: (纸本)9781728142432

Band pass filters play a major role in wireless communication systems. Transmitted and received signals have to be filtered at a certain frequency with a specific bandwidth. In this paper a microstrip parallel coupled-line band pass filter operating at the centre frequency of 3.9 GHz with wide bandwidth of 1.25 GHz is designed and simulated using CST. The proposed bandpass filter is tuned to 3.926 GHz with dimension of 60 mm x 30 mm by adjusting the gap and to 3.861 GHz by adjusting the width between the coupled lines. The filter gives an insertion loss of -2.2 dB, return loss of -17.3 dB and -3 dB bandwidth of 1.25 GHz. The effect of the width and gap of the coupled line on the center frequency is discussed.

关键词： Band-pass filters Microstrip filters Microwave filters Resonator filters Low pass filters Bandwidth Insertion loss

Segmentation Guided HEp-2 Cell Classification with Adversarial Networks

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Segmentation Guided HEp-2 Cell Classification with Adversari...

Computing, Communications and Applications Conference (ComComAp)

作者： Hai Xie Yejun He Haijun Lei Jong Yih Kuo Baiying Lei Guangdong Engineering Research Center of Base Station Antennas and Propagation Shenzhen Key Lab of Antennas and Propagation College of Electronics and Information Engineering Shenzhen University China Guangdong Province Key Laboratory of Popular High-performance Computers School of Computer and Software Engineering Shenzhen University Computer Science and Information Engineering National Taipei University of Technology Taiwan China National-Regional Key Technology Engineering Laboratory for Medical Ultrasound Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging School of Biomedical Engineering Health Science Center Shenzhen University China

ISBN: (数字)9781728119731

ISBN: (纸本)9781728119748

The analysis of indirect immuno fluorescence (IIF) on human epithelial type 2 (HEp-2) cells is of paramount importance for the autoimmune diseases diagnosis. Essentially, accurate segmentation masks can generate rich boundary information, which is beneficial for improving the performance of the classification task For this reason, this paper proposes a novel segmentation guided HEp-2 cell classification method via generative adversarial networks (GANs), which employs the GANs as the segmentor to generate accurate masks for the subsequent classification task. Specifically, the proposed network architecture consists of three modules (i.e., the generator, discriminator and classifier). The first two modules constitute GANs model, which is trained to obtain better segmentation results via playing a min-max game. The segmentation masks and the corresponding original images are fed to the third module together to identify the category of the trained cell. Furthermore, the Xception and ResNet-50 model are used as the backbone of the segmentation and classification network, respectively. Besides, an improved classification loss function via Gaussian Mixture (GM) is proposed to optimize the classification network The proposed architecture can learn rich boundary information and well represent the class label of HEp2 cell images. Experimental results on the HEp-2 International Conference on Pattern Recognition (ICPR) 2016 task1 dataset demonstrate our proposed model achieves quite promising performance.

关键词： Image segmentation computer architecture Task analysis Microprocessors Gallium nitride Feature extraction Generators

A Progressive Background Updating Based Coding Scheme for Surveillance Videos

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A Progressive Background Updating Based Coding Scheme for Su...

IEEE Visual Communications and Image Processing (VCIP)

作者： Meng Li Yunhui Shi Wenpeng Ding Xiaojie Liu Jiaying Liu Baocai Yin Beijing Key Laboratory of Multimedia and Intelligent Software Technology Faculty of Information Technology Beijing University of Technology Beijing China School of Computer Science and Technology Henan Institute of Technology Xinxiang China Peking University Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian China

Background based coding is an effective scheme to improve the coding efficiency of surveillance videos. However, it takes a long time to generate a high quality background picture (BG-picture). And the encoding of the high quality BG-picture will increase the bitrate abruptly. To solve these problems, a progressive background updating based coding scheme is proposed in this paper. In the proposed scheme, the BG-picture is updated block by block. To improve the overall coding efficiency, an importance map is designed to select the valid background blocks (B-blocks) progressively which will be encoded with high quality. It is worth noting that only the valid B-blocks is encoded instead of the entire BG-picture. Compared with the reference software of Versatile Video Coding (VVC), the proposed scheme achieves about 23.3 percent bit-rate saving on average.

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On creating benchmark dataset for aerial image interpretation: Reviews, guidances and million-AID

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arXiv 2020年

作者： Long, Yang Xia, Gui-Song Li, Shengyang Yang, Wen Yang, Michael Ying Zhu, Xiao Xiang Zhang, Liangpei Li, Deren State Key Lab. LIESMARS Wuhan University Wuhan China School of Computer Science State Key Lab. LIESMARS Wuhan University Wuhan China Key Laboratory of Space Utilization Technology and Engineering Center for Space Utilization Chinese Academy of Sciences Beijing China School of Electronic Information State Key Lab LIESMARS Wuhan University Wuhan China Faculty of Geo-Information Science and Earth Observation University of Twente Hengelosestraat 99 Enschede Netherlands Technical University of Munich Germany

The past years have witnessed great progress on remote sensing (RS) image interpretation and its wide applications. With RS images becoming more accessible than ever before, there is an increasing demand for the automatic interpretation of these images. In this context, the benchmark datasets serve as essential prerequisites for developing and testing intelligent interpretation algorithms. After reviewing existing benchmark datasets in the research community of RS image interpretation, this article discusses the problem of how to efficiently prepare a suitable benchmark dataset for RS image interpretation. Specifically, we first analyze the current challenges of developing intelligent algorithms for RS image interpretation with bibliometric investigations. We then present the general guidances on creating benchmark datasets in efficient manners. Following the presented guidances, we also provide an example on building RS image dataset, i.e., Million-AID 1, a new large-scale benchmark dataset containing a million instances for RS image scene classification. Several challenges and perspectives in RS image annotation are finally discussed to facilitate the research in benchmark dataset construction. We do hope this paper will provide the RS community an overall perspective on constructing large-scale and practical image datasets for further research, especially data-driven ones. © 2020, CC BY.

关键词： Remote sensing

A SURVEY OF AUTOMATIC GENERATION OF SOURCE CODE COMMENTS: ALGORITHMS AND TECHNIQUES

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arXiv 2019年

作者： Song, Xiaotao Sun, Hailong Wang, Xu Yan, Jiafei School of Software Taiyuan University of Technology China SKLSDE Lab School of Computer Science and Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing China

As an integral part of source code files, code comments help improve program readability and comprehension. However, developers sometimes do not comment on their program code adequately due to the incurred extra efforts, lack of relevant knowledge, unawareness of the importance of code commenting or some other factors. As a result, code comments can be inadequate, absent or even mismatched with source code, which affects the understanding, reusing and the maintenance of software. To solve these problems of code comments, researchers have been concerned with generating code comments automatically. In this work, we aim at conducting a survey of automatic code commenting researches. First, we generally analyze the challenges and research framework of automatic generation of program comments. Second, we present the classification of representative algorithms, the design principles, strengths and weaknesses of each category of algorithms. Meanwhile, we also provide an overview of the quality assessment of the generated comments. Finally, we summarize some future directions for advancing the techniques of automatic generation of code comments and the quality assessment of comments. Copyright © 2019, The Authors. All rights reserved.

关键词： Surveys

Converting a common document scanner to a multispectral scanner

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arXiv 2019年

作者： Khan, Zohaib Shafait, Faisal Mian, Ajmal Department of Computer Science and Software Engineering University of Western Australia Crawley WA Australia School of Information Technology and Mathematical Sciences University of South Australia Adelaide SA Australia Islamabad Pakistan

We propose the construction of a prototype scanner designed to capture multispectral images of documents. A standard sheet-feed scanner is modified by disconnecting its internal light source and connecting an external multispectral light source comprising of narrow band light emitting diodes (LED). A document is scanned by illuminating the scanner light guide successively with different LEDs and capturing a scan of the document. The system is portable and can be used for potential applications in verification of questioned documents, cheques, receipts and bank notes. Copyright © 2019, The Authors. All rights reserved.

关键词： Scanning

M-generalization for multipurpose transactional data publication

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Frontiers of computer Science 2018年第6期12卷 1241-1254页

作者： Xianxian LI Peipei SUI Yan BAI Li-E WANG School of Computer Science and Engineering Beihang UniversityBeijing 100191China Guangxi Key Lab of Multi-source Information Mining &Security Guangxi Normal UniversityGuilin 541004China Institute of Technology University of Washington TacomaTacoma WA 98402-3100USA

Transactional data collection and sharing currently face the challenge of how to prevent information leakage and protect data from privacy breaches while maintaining high-quality data utilities. Data anonymization methods such as perturbation, generalization, and suppression have been proposed for privacy protection. However, many of these methods incur excessive information loss and cannot satisfy multipurpose utility requirements. In this paper, we propose a multidimensional generalization method to provide multipurpose optimization when anonymizing transactional data in order to offer better data utility for different applications. Our methodology uses bipartite graphs with generalizing attribute, grouping item and perturbing outlier. Experiments on real-life datasets are performed and show that our solution considerably improves data utility compared to existing algorithms.

关键词： anonymization generalization privacy protection bipartite graph

Design and Development of Android Application for Educational Institutes

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Journal of Physics: Conference Series 2021年第1期1769卷

作者： Chukwuebuka Joseph Ejiyi Jianhua Deng Thomas Ugochukwu Ejiyi Adetunji A Salako Makuachukwu B Ejiyi Chinonso G Anomihe School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu PRC Department of Pure and Industrial Chemistry University of Nigeria Nsukka Enugu State Nigeria School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu PRC Department of Agricultural Extensions University of Nigeria Nsukka Enugu State Nigeria Department of Biochemistry Federal University of Technology Owerri Imo State Nigeria

The growth in the use android applications (Apps) has made it the most popular smart device operating system in use nowadays. Android has over 76% of the mobile operating system from December 2018–January 2020 which is quite significant. Android phones are also becoming the most used electronics globally. Students of higher institutions of learning are also becoming accustomed to the use of applications such that they want everything available for them on their mobile device if possible. This paper deals on an android application that will aid students in planning their timetable and scheduling their classes as well as having full knowledge of days according to the school calendar, get access to academic resources and information about the school right on their smart devices. From the application, one can have access to the detailed and accurate information of the school.

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