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arXiv 2020年

作者： Lin, Jinghuang Cheng, Zhanzhan Bai, Fan Niu, Yi Pu, Shiliang Zhou, Shuigeng Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University Shanghai200433 China Hikvision Research Institute China

Scene text recognition (STR) is still a hot research topic in computer vision field due to its various applications. Existing works mainly focus on learning a general model with a huge number of synthetic text images to recognize unconstrained scene texts, and have achieved substantial progress. However, these methods are not quite applicable in many real-world scenarios where 1) high recognition accuracy is required, while 2) labeled samples are lacked. To tackle this challenging problem, this paper proposes a few-shot adversarial sequence domain adaptation (FASDA) approach to build sequence adaptation between the synthetic source domain (with many synthetic labeled samples) and a specific target domain (with only some or a few real labeled samples). This is done by simultaneously learning each character’s feature representation with an attention mechanism and establishing the corresponding character-level latent subspace with adversarial learning. Our approach can maximize the character-level confusion between the source domain and the target domain, thus achieves the sequence-level adaptation with even a small number of labeled samples in the target domain. Extensive experiments on various datasets show that our method significantly outperforms the finetuning scheme, and obtains comparable performance to the state-of-the-art STR methods. Copyright © 2020, The Authors. All rights reserved.

关键词： Character recognition

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A Novel Sensitization Mechanism of Stress-Electric-Coupled Biosensor Originated in Magnetostrictive Effect

SSRN

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SSRN 2022年

作者： Sang, Shengbo Ge, Yang Ji, Jianglong Yuan, Zhongyun Dong, Xiushan Zhou, Chuangang Xiao, Pengli Tan, Qiuyun Zhao, Dong MicroNano System Research Center Key Lab of Advanced Transducers and Intelligent Control System The Ministry of Education College of Information and Computer Taiyuan University of Technology Taiyuan030024 China School of Electrical Engineering College of Engineering Science Hanyang University Seoul04763 Korea Republic of Shanxi Bethune Hospital Taiyuan030024 China Six-dimensional Artificial Intelligence Biomedical Research Institute Taiyuan030024 China

The stress-electric coupling based on receptor functionalization provides a new paradigm for the development of biosensor. However, the gravity factor of sensitive element usually shows difficult to be avoided due to its suppression to biosensor sensitivity. Herein, a magnetic-sensitization biosensing system with multi-physical field coupling of stress, magnetism and electricity was proposed to highly detect biomolecules. The gravitational interference of sensitive membrane was conquered by doping the TbDyFe with magnetostrictive effect into polydimethylsiloxane (PDMS) and applying magnetic field, showing great contributions to magnetic sensitization. The magnetic sensitization of the biosensor was proved by the collaboration of experiment and simulation. The detections of urine protein and urine sugar associated with kidney disease were realized with limits of detection (LOD) of 0.21 ng/mL and 0.45 nM by using the magnetic-sensitization biosensor. The prepared biosensor exhibited the high specificity, selectivity, stability and repeatability. Especially, the HSA and glucose in real samples can be accurately detect, showing good practicability of the prepared biosensor. This study provides a way to improve the sensitivity of the mechanical biosensor. © 2022, The Authors. All rights reserved.

关键词： Silicones

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Universal deep network for steganalysis of color image based on channel representation

arXiv

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arXiv 2021年

作者： Wei, Kangkang Luo, Weiqi Tan, Shunquan Huang, Jiwu The Guangdong Key Lab of Information Security Technology School of Computer Science and Engineering Sun Yat-Sen University Guangzhou510006 China The College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China The Guangdong Key Laboratory of Intelligent Information Processing Shenzhen Key Laboratory of Media Security National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen518060 China

Up to now, most existing steganalytic methods are designed for grayscale images, and they are not suitable for color images that are widely used in current social networks. In this paper, we design a universal color image steganalysis network (called UCNet) in spatial and JPEG domains. The proposed method includes preprocessing, convolutional, and classification modules. To preserve the steganographic artifacts in each color channel, in preprocessing module, we firstly separate the input image into three channels according to the corresponding embedding spaces (i.e. RGB for spatial steganography and YCbCr for JPEG steganography), and then extract the image residuals with 62 fixed high-pass filters, finally concatenate all truncated residuals for subsequent analysis rather than adding them together with normal convolution like existing CNN-based steganalyzers. To accelerate the network convergence and effectively reduce the number of parameters, in convolutional module, we carefully design three types of layers with different shortcut connections and group convolution structures to further learn high-level steganalytic features. In classification module, we employ a global average pooling and fully connected layer for classification. We conduct extensive experiments on ALASKA II to demonstrate that the proposed method can achieve state-of-the-art results compared with the modern CNN-based steganalyzers (e.g., SRNet and J-YeNet) in both spatial and JPEG domains, while keeping relatively few memory requirements and training time. Furthermore, we also provide necessary descriptions and many ablation experiments to verify the rationality of the network design. Copyright © 2021, The Authors. All rights reserved.

关键词： Steganography

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An axial-ratio beam-width enhancement of antenna based on electromagnetic bandgap (EBG)

An axial-ratio beam-width enhancement of antenna based on el...

引用

IEEE information Technology, Networking, Electronic and Automation Control Conference

作者： Shijie Huang Liang Zhang Chao Wang Changqing Liu Shenbing Wu Xianliang Wu Key Lab of Intelligent Computing & Signal Processing Ministry of Education Anhui University AnHui Province Key Laboratory of simulation and design for Electronic information system Hefei Normal university Hefei China

ISBN: (数字)9781728143903

ISBN: (纸本)9781728143910

In order to meet the requirements of the navigation system for antennas with wide 3-dB AR beam-width, this paper proposes an axial-ratio beam-width enhancement of antenna based on electromagnetic bandgap (EBG). The effect of surface wave on the circular polarization of the antenna is suppressed by loading two layers of mushroom-like EBG unit cells around the patch. The loading of the EBG increases the 3-dB AR beam-width of the antenna by 78% in the xoz plane and the by 84% in the yoz plane, the simulation and test results demonstrate the effectiveness of this method.

关键词：

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research on Influence of Content Diversity on Full-Reference Image Quality Assessment 16th

Research on Influence of Content Diversity on Full-Reference...

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16th International Forum on Digital TV and Wireless Multimedia Communication, IFTC 2019

作者： Zhang, Huiqing Li, Shuo Xia, Zhifang Chen, Weiling Tang, Lijuan Faculty of Information Technology Beijing University of Technology Beijing100124 China Engineering Research Center of Digital Community Ministry of Education Beijing100124 China The State Information Center of China Beijing100045 China Fujian Key Lab for Intelligent Processing and Wireless Transmission of Media Information Fuzhou University Fuzhou350000 China Jiangsu Vocational College of Business Jiangsu226000 China

ISBN: (纸本)9789811533402

With the development of image quality assessment (IQA), the full-reference (FR) IQA algorithms are becoming more and more mature. This paper analyzes the performance of five FR natural scene (NS) IQA algorithms and three FR screen content (SC) IQA algorithms, and makes analysis on the eight IQA algorithms in terms of prediction performance and design principle. Experiments show, (1) the performance of perceptual similarity based IQA method proposed by Gu et al. is better;(2) the multi-scale technology plays an important role in improving the performance of algorithms. Finally, summarized and expounded the development direction of image quality evaluation. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Quality control

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Low Profile Dual-Band Antenna on an EBG Substrate

Low Profile Dual-Band Antenna on an EBG Substrate

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IEEE International Wireless Symposium (IWS)

作者： Shijie Huang Liang Zhang Chao Wang Changqing Liu Yifan Jiang Xianliang Wu Key Lab of Intelligent Computing & Signal Processing Ministry of Education Anhui University AnHui Province Key Laboratory of simulation and design for Electronic information system Hefei Normal university Hefei China

ISBN: (数字)9781728167039

ISBN: (纸本)9781728167046

This paper proposes a dual-band antenna based on the electromagnetic band gap structure suitable for WLAN communication systems. The proposed antenna is designed to work at 2.45/5.8 GHz WLAN band. By loading the EBG structure directly below a dual-frequency monopole antenna, the in-phase superposition of electromagnetic waves at the center frequency of the antenna is achieved. The antenna exhibits high gains of near 8.0 and 12.0 dB at the low and high working frequencies while maintaining the low profile characteristics.

关键词： Wireless LAN Directive antennas Reflector antennas Metamaterials Loaded antennas Gain Periodic structures

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A circularly polarized low-profile Metasurface antenna based on CPW feed

A circularly polarized low-profile Metasurface antenna based...

引用

IEEE International Wireless Symposium (IWS)

作者： Changqing Liu Liang Zhang Shijie Huang Chao Wang Xingchuan Yu Xianliang Wu Key Lab of Intelligent Computing & Signal Processing Ministry of Education Anhui University AnHui Province Key Laboratory of simulation and design for Electronic information system Hefei Normal university Hefei China

ISBN: (数字)9781728167039

ISBN: (纸本)9781728167046

A low-profile circularly polarized Metasurfaces antenna based on compact coplanar waveguide (CPW) feed was proposed. The Metasurfaces consists of 16 periodic square-cut metal patches. An hourglass coupled slot was adopted to achieve broadband impedance matching. The antenna has a simple structure and a low cross section, and it can be implemented by a layer of a printed circuit substrate. A circular polarized wave is generated by changing the size of the cut angle of the Metasurfaces, and at the same time, the impedance bandwidth can be widened. To verify the simulation results, a 1λ 0 ×1λ 0 ×0.05λ 0 (at 10 GHz) model antenna was fabricated and measured. The simulation and measurement results show good consistency. The test results show that the -10dB return loss bandwidth reaches 45.3 %, and the circular polarization axis ratio(AR) is less than 3dB with a bandwidth of 18.5%.

关键词： Antenna measurements Polarization Bandwidth Metasurfaces Radar antennas Antenna feeds Coplanar waveguides

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12-Port Hybrid MIMO Antenna Array for 5G Smartphone Applications

12-Port Hybrid MIMO Antenna Array for 5G Smartphone Applicat...

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IEEE International Wireless Symposium (IWS)

作者： Peng Liu Yufa Sun Bingbing Chen Key Lab of Intelligent Computing & Signal Processing Ministry of Education Anhui University Anhui Province Key Laboratory of simulation and design for Electronic information system Hefei Normal University Hefei China

ISBN: (数字)9781728167039

ISBN: (纸本)9781728167046

A hybrid twelve-antenna array operating in the 3.3-3.6 GHz and 4.8-5.0 GHz band for multiple input multiple output (MIMO) applications in 5G smartphones is proposed. The proposed hybrid antenna array elements are symmetrically placed along the long edges of the smartphone, and they are composed of two inverted-F antennas (IFA) with different structural parameters. Simulated antenna isolation is better than -14.5 dB without any decoupling structures. Moreover, simulated radiation patterns, antenna efficiencies, and envelop correlation coefficients are also given in the paper.

关键词： Wireless communication 5G mobile communication Structural engineering Smart phones MIMO communication Antenna arrays Antenna radiation patterns

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Bayesian dual neural networks for recommendation

引用

Frontiers of Computer Science 2019年第6期13卷 1255-1265页

作者： Jia HE Fuzhen ZHUANG Yanchi LIU Qing HE Fen LIN Key Lab of Intelligent Information Processing of Chinese Academy of Sciences Institute of Computing TechnologyChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China Rutgers University Newark 07102USA Search Product Center WeChat Search Application DepartmentTencentBeijing 100080China

Most traditional collaborative filtering(CF)methods only use the user-item rating matrix to make recommendations,which usually suffer from cold-start and sparsity *** address these problems,on the one hand,some CF methods are proposed to incorporate auxiliary information such as user/item profiles;on the other hand,deep neural networks,which have powerful ability in learning effective representations,have achieved great success in recommender ***,these neural network based recommendation methods rarely consider the uncertainty of weights in the network and only obtain point estimates of the ***,they maybe lack of calibrated probabilistic predictions and make overly confident *** this end,we propose a new Bayesian dual neural network framework,named BDNet,to incorporate auxiliary information for ***,we design two neural networks,one is to learn a common low dimensional space for users and items from the rating matrix,and another one is to project the attributes of users and items into another shared latent *** that,the outputs of these two neural networks are combined to produce the final ***,we introduce the uncertainty to all weights which are represented by probability distributions in our neural networks to make calibrated probabilistic *** experiments on real-world data sets are conducted to demonstrate the superiority of our model over various kinds of competitors.

关键词： collaborative filtering Bayesian neural network hybrid recommendation algorithm

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Learning to Undersampling for Class Imbalanced Credit Risk Forecasting

Learning to Undersampling for Class Imbalanced Credit Risk F...

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IEEE International Conference on Data Mining (ICDM)

作者： Jianfeng Chi Guanxiong Zeng Qiwei Zhong Ting Liang Jinghua Feng Xiang Ao Jiayu Tang Alibaba Group CN Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing CN University of Chinese Academy of Sciences Beijing CN

ISBN: (数字)9781728183169

ISBN: (纸本)9781728183176

Credit risk forecasting generally aims to evaluate the default probability of users in financial service. It is usually regarded as a binary classification problem, which suffers from the severe class-imbalance problem due to the extremely limited throngs and the concept drift problem brought by the delayed verification. In this paper, we investigate these problems in credit risk forecasting and propose a semi-supervised meta-learning based approach called TRUST (TRainable Undersampling with Self Training) to resolve. First, it decides whether to sample the data through meta-learning based reinforcement learning. Secondly, it learns the distribution of the data that have not yet shown financial performance via self-training and updates the model trained in the first step. Finally, the updated model is evaluated on the validation dataset, the result of which will be fed back through the evaluator. These three steps will be iterated until the model converges. With the real-world industrial dataset containing 1.75 million users, we investigate the effectiveness of our method. Experimental results exhibit that the proposed method is able to improve AP over 5.94% on credit risk forecasting task compared with the recent methods.

关键词： Training Reinforcement learning Data models Data mining Forecasting Task analysis Financial services

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