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4th International Conference on Fuzzy Systems and Data Mining, FSDM 2018

作者： Cheng, Hong Wang, Jincheng Shen, Chuan Zhang, Cheng Zhang, Fen Bao, Wenxia Education Ministry Key Laboratory of Intelligent Computing and Signal Processing Anhui University HefeiAnhui230039 China

ISBN: (纸本)9781614999270

In order to effectively recover the phase information of the object and reconstruct the three-dimensional shape of the object, a multiplicative reconstruction based on the transport of intensity equation (TIE) is proposed. Firstly, combining with the relationship between the light field moment imaging and the TIE, the phase information and the first moments of the light field are solved between the two differently focused intensity images, and the phase perspective can be recovered. In this way, the phase can be observed from different slight angles, and the three-dimensional shape of the phase of the object is reconstructed in combination with the multiplicative technique . At the same time, the object is rotated at different angles for the purpose of reconstructing the three-dimensional shape of the object phase under these angles. Finally, the correctness and effectiveness of the algorithm are verified by experimental results. © 2018 The authors and IOS Press. All rights reserved.

关键词： Fuzzy systems

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New Framework for Code-Mapping-based Reversible Data Hiding in JPEG Images

arXiv

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arXiv 2020年

作者： Du, Yang Yin, Zhaoxia Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei230601 China Anhui Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University Hefei230601 China School of Communication & Electronic Engineering East China Normal University Shanghai200241 China

Code mapping (CM) is an efficient technique for reversible data hiding (RDH) in JPEG images, which embeds data by constructing a mapping relationship between the used and unused codes in the JPEG bitstream. This study presents a new framework for designing a CM-based RDH method. First, a new code mapping strategy is proposed to suppress file size expansion and improve applicability. Based on our proposed strategy, the mapped codes are redefined by creating a new Huffman table rather than selecting them from the unused codes in the original Huffman table. The critical issue of designing the CM-based RDH method, that is, constructing code mapping, is converted into a combinatorial optimization problem. This study proposes a novel CM-based RDH method that utilizes a genetic algorithm (GA). The experimental results demonstrate that the proposed method achieves a high embedding capacity with no signal distortion while suppressing file size expansion. Copyright © 2020, The Authors. All rights reserved.

关键词： Mapping

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dense feature aggregation and pruning for RGBT tracking

arXiv

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arXiv 2019年

作者： Zhu, Yabin Li, Chenglong Luo, Bin Tang, Jin Wang, Xiao Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei Anhui China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Institute of Physical Science and Information Technology Anhui University Hefei Anhui China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Key Laboratory of Industrial Image Processing and Analysis of Anhui Province Hefei Anhui China

How to perform effective information fusion of different modalities is a core factor in boosting the performance of RGBT tracking. This paper presents a novel deep fusion algorithm based on the representations from an end-to-end trained convolutional neural network. To deploy the complementarity of features of all layers, we propose a recursive strategy to densely aggregate these features that yield robust representations of target objects in each modality. In different modalities, we propose to prune the densely aggregated features of all modalities in a collab.rative way. In a specific, we employ the operations of global average pooling and weighted random selection to perform channel scoring and selection, which could remove redundant and noisy features to achieve more robust feature representation. Experimental results on two RGBT tracking benchmark datasets suggest that our tracker achieves clear state-of-the-art against other RGB and RGBT tracking methods. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

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cmSalGAN: RGB-D salient object detection with cross-view generative adversarial networks

arXiv

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arXiv 2019年

作者： Jiang, Bo Zhou, Zitai Wang, Xiao Tang, Jin Key Laboratory of Intelligent Computing Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei230601 China

Image salient object detection (SOD) is an active research topic in computer vision and multimedia area. Fusing complementary information of RGB and depth has been demonstrated to be effective for image salient object detection which is known as RGB-D salient object detection problem. The main challenge for RGB-D salient object detection is how to exploit the salient cues of both intra-modality (RGB, depth) and cross-modality simultaneously which is known as cross-modality detection problem. In this paper, we tackle this challenge by designing a novel cross-modality Saliency Generative Adversarial Network (cmSalGAN). cmSalGAN aims to learn an optimal view-invariant and consistent pixel-level representation for RGB and depth images via a novel adversarial learning framework, which thus incorporates both information of intra-view and correlation information of cross-view images simultaneously for RGB-D saliency detection problem. To further improve the detection results, the attention mechanism and edge detection module are also incorporated into cmSalGAN. The entire cmSalGAN can be trained in an end-to-end manner by using the standard deep neural network framework. Experimental results show that cmSalGAN achieves the new state-of-the-art RGB-D saliency detection performance on several benchmark datasets. Copyright © 2019, The Authors. All rights reserved.

关键词： Generative adversarial networks

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An Overlapping Community Detection Based Multi-Objective Evolutionary Algorithm for Diversified Social Influence Maximization

An Overlapping Community Detection Based Multi-Objective Evo...

引用

Congress on Evolutionary Computation

作者： Lei Zhang Fengiiao Sun Fan Cheng Haiping Ma Xiaoyan Sun Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei China Institutes of Physical Science and Information Technology Anhui University Hefei China School of Information and Control Engineering China University of Mining and Technology Xuzhou China

ISBN: (数字)9781728169293

ISBN: (纸本)9781728169309

Influence maximization refers to selecting a group of nodes from a social network, which obtains the largest influence spread under a cascade model. However, most of the existing works only focused on the influence and ignored the diversity of influenced crowd. Thus, scholars have raised the issue of diversified social influence maximization recently, using the category information of nodes to design diversity indicator and introducing a trade-off parameter to balance the two objectives influence and diversity as one single objective for optimization. In fact, the category information of nodes in the network is usually difficult to be collected, thus the definition of diversity based on nodes' categories is not very general and accurate. In addition, it is very difficult to set the trade-off parameter, especially when there is no prior knowledge in real applications. To this end, we employ overlapping community structure information to design the diversity of nodes without any node's additional (e.g. category) information. Due to the two objectives of influence and diversity may be conflicting, a multi-objective evolutionary algorithm named MOEA-DIM is proposed to optimize the two objectives simultaneously, which does not need to set the tradeoff parameter between the two objectives. In MOEA-DIM, a network reduction strategy based on overlapping community structure is suggested to greatly reduce the search space. In addition, a population initialization strategy based on random walk is designed to accelerate the convergence of the algorithm. Experiments on six real-world datasets show that the proposed algorithm MOEA-DIM has promising performance in terms of both effectiveness and efficiency.

关键词： Optimization Encoding

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Design of Filtering Power Divider with Wide Stopband Based on QMSIW

引用

Journal of Physics: Conference Series 2020年第1期1651卷

作者： Yi Cheng Zhixiang Huang Zhongmiao Wang Chao Wang Xuemei Li Key Lab of Ministry of Education of Intelligent Computing & Signal Processing Anhui University Hefei Anhui 230601 China

A miniaturized filtering power divider with wide stopband based on quarter-mode substrate integrated waveguide (QMSIW) is proposed. The physical size of the QMSIW is reduced by 3/4 comparing with the traditional SIW structure, which can achieve miniaturization, and its electromagnetic field distribution has little effect. Using the metal interference column and the etched U-shaped groove to adjust the resonance frequency, so that the main mode and the first higher mode form a passband, meanwhile, suppressing the second higher mode. The simulation results show that the center frequency is 4.42 GHz with insertion loss of 0.45 dB, the 3-dB bandwidth is 4.12-4.63 GHz with a fractional bandwidths of 9.7%, and there is a great stopband up to 11 GHz with 15 dB rejection level. Besides, the return loss of passband is better than 17.5 dB. To verify the validity of this design, a prototype is fabricated and measured. The measured results demonstrate that it has a good agreement with the design simulations.

关键词：

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Bilingual Word Embedding with Sentence Combination CNN for 1-to-N Sentence Alignment 20

Bilingual Word Embedding with Sentence Combination CNN for 1...

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Proceedings of the 4th International Conference on Natural Language processing and Information Retrieval

作者： Xinyuan Ren Xiangling Fu Xuesi Zhou Chunsheng Liu Songfeng Gao Lei Peng School of Software Engineering Beijing University of Posts and Telecommunications Beijing China and Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education Beijing University of Posts and Telecommunications Beijing China Department of Electronic Engineering Tsinghua University Hai Dian Beijing China and Multimedia Signal and Intelligent Information Processing Lab Tsinghua University Hai Dian Beijing China BUPT and Huarong Joint lab of Smart Finance Beijing P. R. China and HuaRong RongTong (Beijing) Technology Co. Ltd Beijing P. R. China

ISBN: (纸本)9781450377607

Sentence alignment, as one of the most active and fundamental tasks in the field of natural language processing (NLP), is usually realized in two categories of methods. One is traditional methods which are firstly proposed, the other, which are adopted later, is based on the Neural Network method. Presently, under the limitation that the existing mainstream data corpora are mostly in the form of 1-to-1, the alignment models with relatively good performance mainly apply to the cases of 1-to-1 sentence alignment. However, under the circumstance that a sentence contains too much information, 1-to-N sentence alignment can actually have a better effect on sentence translation tasks, compared with the 1-to-1 form, since it is more flexible and can reduce the complexity of the original sentence. As a result, we attempt to exploit neural networks with relatively good performance in the cases of 1-to-1 to fit in the cases of 1-to-N. In this paper, a novel 1-N Bilingual word Embedding with Sentence Combination CNN Improved Framework (1-NBESCC) is proposed in order to align 1-to-N sentences more precisely. Experiments show that our proposed model performs as good as the traditional methods such as BLEUALIGN in 1-to-1 situation, but much better in 1-to-N situation.

关键词： Convolutional Neural Network

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Solving Electromagnetic Scattering from Microstrip Arrays with Multiple-Traces Surface Integral Equations

Solving Electromagnetic Scattering from Microstrip Arrays wi...

引用

2018 IEEE International Conference on Computational Electromagnetics, ICCEM 2018

作者： Zhao, Ran Feng, Jian Song, Kaihong Huang, Zhixiang Hu, Jun Anhui University Ministry of Education Key Laboratory of Intelligent Computing and Signal Processing China School of Electronic Engineering China

ISBN: (纸本)9781538612415

In this paper, a new multiple-traces Poggio-Miller-Chang-Harrington-Wu-Tsai (MT-PMCHWT) equation is proposed to simulate the electromagnetic scattering from microstrip structures. Different from traditional EFIE-PMCHWT method, in this new multiple-traces method, the original object can be decomposed into two independent domains i.e., the exterior region (free space) and interior region (microstrip), and Robin transmission conditions (TCs) is enforced on the interface between exterior and interior regions to ensure the continuity of fields. In comparison to the traditional EFIE-PMCHWT, this new MT-PMCHWT has a better convergence property. Because the continuity of fields is ensured by TCs, the exterior and interior regions can be discretized by non-conformal meshes, which improves the flexibility and efficiency of the proposed methods substantially. © 2018 IEEE.

关键词： Surface scattering

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Design of New Miniaturized Broadband Bandpass Filter Based on SIR

Design of New Miniaturized Broadband Bandpass Filter Based o...

引用

Progress in Electromagnetics Research Symposium - Fall (PIERS - FALL)

作者： Kaiyue Duan Pingjuan Zhang Dongya Cheng Yawen Song Lichang Huang Minquan Li Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China Anhui Science and Technology University Hefei China

ISBN: (数字)9781728153049

ISBN: (纸本)9781728153056

In this paper, a compact and miniaturized wideband bandpass filter based on resonant ring loading stepped impedance resonator is designed. The filter designed in this paper uses the resonant ring as the basic resonator unit. By loading the SIR, the passband width of the filter is improved. The 3 dB bandwidth of this filter is 300 MHz, and the relative fractional bandwidth is 15%. Etching a complementary open resonant ring defected ground structure (DGS) on the floor that changes the current distribution on the floor and creates a band gap with passband characteristics, making the filter compact and compact. The size of filter is 3.5 cm * 4.0 cm. The simulation results show that the filter center frequency is 2.0 GHz, the return loss is 29 dB, and the insertion loss is 1.1 dB. The filter introduces two transmission zero points of 1.3 GHz and 2.6 GHz on both sides of the passband, which improves the out-of-band rejection of the filter. The filter structure designed in this paper has the advantages of small size, wide bandwidth and strong stop band rejection, which verifies the feasibility of the filter design.

关键词： Bandwidth Broadband communication Impedance Passband Resonant frequency Microstrip Filtering theory

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Broadband Circular Polarized Composite Spiral Antenna Using Two-layer AMC

Broadband Circular Polarized Composite Spiral Antenna Using ...

引用

Progress in Electromagnetics Research Symposium - Fall (PIERS - FALL)

作者： Yawen Song Pingjuan Zhang Yanyang Liu Kaiyue Duan Lichang Huang Minquan Li Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China Anhui Science and Technology University Hefei China

ISBN: (数字)9781728153049

ISBN: (纸本)9781728153056

In this paper, a broadband circular polarized (CP) composite spiral antenna using two-layer artificial magnetic conductor (AMC) is designed. The broadband circularly polarized radiation of the antenna in free space is realized by combining Archimedes spiral and equiangular spiral. At the same time, a new two-layer AMC structure is designed to improve the degradation of axial ratio and bandwidth caused by unidirectional antenna radiation in some frequency bands. The two-layer AMC is designed to operate with 90° reflection-phase bandwidth of 4.3-6 GHz (33%). Three different reflector surfaces: perfect electric conductor (PEC), traditional single-layer AMC surface and two-layer AMC surface are used and compared. The axial ratio performance of the antenna loaded with two-layer AMC is significantly better than that of the traditional AMC in the band of 5-6.5 GHz. The axial ratio and bandwidth was further improved by removing the central patch on the two-layer AMC surface and adding a high dielectric substrate underneath. The simulation results show that in the 2.5-10 GHz working band, the VSWR

关键词： Spirals Broadband antennas Bandwidth Loaded antennas Periodic structures Helical antennas

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