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arXiv 2020年

作者： Yu, Zhuoping Gao, Zhong Chen, Hansheng Huang, Yuyao Institute of Intelligent Vehicles School of Automotive Studies Tongji University Shanghai China State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body China

For vehicles equipped with the automatic parking system, the accuracy and speed of the parking slot detection are crucial. But the high accuracy is obtained at the price of low speed or expensive computation equipment, which are sensitive for many car manufacturers. In this paper, we proposed a detector using CNN(convolutional neural networks) for faster speed and smaller model size while keeps accuracy. To achieve the optimal balance, we developed a strategy to select the best receptive fields and prune the redundant channels automatically after each training epoch. The proposed model is capable of jointly detecting corners and line features of parking slots while running efficiently in real time on average processors. The model has a frame rate of about 30 FPS on a 2.3 GHz CPU core, yielding parking slot corner localization error of 1.51±2.14 cm (std. err.) and slot detection accuracy of 98%, generally satisfying the requirements in both speed and accuracy on on-board mobile terminals. Copyright © 2020, The Authors. All rights reserved.

关键词： Convolution

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Semi-vortex solitons and their excited states in spin-orbit-coupled binary bosonic condensates

arXiv

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arXiv 2024年

作者： Deng, Haiming Li, Jinqing Chen, Zhaopin Liu, Yaohui Liu, Dong Jiang, Chunzhi Kong, Chao Malomed, Boris A. School of Physics and Electronic-Electrical Engineering Xiangnan University Chenzhou423000 China Microelectronics and Optoelectronics Technology Key Laboratory of Hunan Higher Education Xiangnan University Chenzhou423000 China Hunan Engineering Research Center of Advanced Embedded Computing and Intelligent Medical Systems Xiangnan University Chenzhou423000 China Physics Department Solid-State Institute Technion Haifa32000 Israel Department of Physical Electronics School of Electrical Engineering Faculty of Engineering Tel Aviv University Tel Aviv69978 Israel Instituto de Alta Investigación Universidad de Tarapacá Casilla 7D Arica Chile

It is known that two-dimensional two-component fundamental solitons of the semi-vortex (SV) type, with vorticities (s+, s−) = (0, 1) in their components, are stable ground states (GSs) in the spin-orbit-coupled (SOC) binary Bose-Einstein condensate with the contact self-attraction acting in both components, in spite of the possibility of the critical collapse in the system. However, excited states (ESs) of the SV solitons, with the vorticity set (s+, s−) = (S+, S+ + 1) and S+ = 1, 2, 3, ..., are unstable in the same system. We construct ESs of SV solitons in the SOC system with opposite signs of the self-interaction in the two components. The main finding is stability of the ES-SV solitons, with the extra vorticity (at least) up to S+ = 6. The threshold value of the norm for the onset of the critical collapse, Nthr, in these excited states is higher than the commonly known critical value, Nc ≈ 5.85, associated with the single-component Townes solitons, Nthr increasing with the growth of S+. A velocity interval for stable motion of the GS-SV solitons is found too. The results suggest a solution for the challenging problem of the creation of stable vortex solitons with high topological charges. Copyright © 2024, The Authors. All rights reserved.

关键词： Excited states

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Dual space multi-granular model for multi-interest sequential recommendation

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Knowledge-Based Systems 2025年 323卷

作者： Yijun Sheng Puiieng Lei Yanyan Liu Ximing Chen Qiwen Xu Zhiguo Gong State Key Laboratory of Internet of Things for Smart City University of Macau 999078 Macao Special Administrative Region of China Guangdong-Macau Joint Laboratory for Advanced and Intelligent Computing University of Macau 999078 Macao Special Administrative Region of China Department of Computer Information Science University of Macau 999078 Macao Special Administrative Region of China

Sequential recommendation aims to predict the next item for a user given his historical interaction sequence. Recently, multi-interest and Graph Neural Network (GNN) based paradigms are two new directions in such task. Multi-interest learning encompasses extracting diverse user interests through historical item clustering, while GNN refines user preferences through correlations among historical items. Recent research suggests the synergistic potential of combining these methods to aggregate user preferences at multiple levels, enhancing the accuracy of multi-interest extraction for improved recommendations. However, existing GNN-based multi-interest models can only achieve local smoothing for node embeddings through neighbor information aggregating, thus, they could not match remote items (far-apart items on the item–item graph) even though those remote items show similar local patterns and the items may reflect some niche preferences. It is unreasonable in the context of multi-interest recommendation as the objective is to capture the user’s interests in a more comprehensive manner. To tackle this issue, we propose a D ual S pace M ulti- G ranular Rec ommendation model ( DSMGRec ), where a Graph Deconvolutional Network (GDcN) is designed to disentangle local structure-based patterns of items as their additional embeddings. Then, we adopt a dual framework that combines the traditional GNN with our novel GDcN to encode multi-granular representations for items in the dual space. Such dual item representations can match items by not only their primary patterns but also their secondary patterns. Experiments on four real-world datasets with different densities show that our model outperforms state-of-the-art baselines.

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Nonreciprocal Single-Photon Band Structure

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Physical Review Letters 2022年第20期128卷 203602-203602页

作者： Jiang-Shan Tang Wei Nie Lei Tang Mingyuan Chen Xin Su Yanqing Lu Franco Nori keyu Xia College of Engineering and Applied Sciences National Laboratory of Solid State Microstructures and Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing 210023 China School of Physics Nanjing University Nanjing 210023 China RIKEN Quantum Computing Center RIKEN Cluster for Pioneering Research Wako-shi Saitama 351-0198 Japan Center for Joint Quantum Studies and Department of Physics School of Science Tianjin University Tianjin 300350 China School of Electronic Science and Engineering Nanjing University Nanjing 210023 China Physics Department The University of Michigan Ann Arbor Michigan 48109-1040 USA Jiangsu Key Laboratory of Artificial Functional Materials Nanjing University Nanjing 210023 China Key Laboratory of Intelligent Optical Sensing and Manipulation (Nanjing University) Ministry of Education Nanjing 210023 China

We study a single-photon band structure in a one-dimensional coupled-resonator optical waveguide that chirally couples to an array of two-level quantum emitters (QEs). The chiral interaction between the resonator mode and the QE can break the time-reversal symmetry without the magneto-optical effect and an external or synthetic magnetic field. As a result, nonreciprocal single-photon edge states, band gaps, and flat bands appear. By using such a chiral QE coupled-resonator optical waveguide system, including a finite number of unit cells and working in the nonreciprocal band gap, we achieve frequency-multiplexed single-photon circulators with high fidelity and low insertion loss. The chiral QE-light interaction can also protect one-way propagation of single photons against backscattering. Our work opens a new door for studying unconventional photonic band structures without electronic counterparts in condensed matter and exploring its applications in the quantum regime.

关键词： Cavity quantum electrodynamics Light propagation, transmission & absorption Quantum description of light-matter interaction Topological effects in photonic systems

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RCGA-Net: An Improved Multi-hybrid Attention Mechanism Network in Biomedical Image Segmentation

RCGA-Net: An Improved Multi-hybrid Attention Mechanism Netwo...

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2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021

作者： Xiao, Feng Shen, Cong Chen, Yu Yang, Tian Chen, Shengyong Liao, Zhijun Tang, Jijun Tianjin University of Technology School of Computer Science and Engineering Tianjin China Engineering Research Center of Learning-Based Intelligent System Ministry of Education Tianjin China School of Basic Medical Sciences Fujian Medical University Fujian Fuzhou China College of Intelligence and Computing Tianjin University Tianjin China Key Laboratory of Systems Bioengineering Ministry of Education Tianjin China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen China Department of Computer Science and Engineering University of South Carolina ColumbiaSC United States

ISBN: (纸本)9781665401265

Drawing support from an effective Medical Image Segmentation (MIS) is conducive to a substantial diagnostic basis for the physicians to identify the focus lesion in the patient body and give the subsequent clinical assessment of the patient status. Although various works have tried the challenging quantitative analysis problem, it is still difficult to conduct precise automatic segmentation, especially the soft tissue organs. In this decade, with the increased amount of available datasets, deep learning-based networks have achieved remarkable performance in image processing. Inspired by the state-of-the-art deep learning works, in this paper, we propose an end-to-end multi-layer network named RCGA-Net. It consists of an encoder-decoder backbone that integrates a coordinate attention mechanism based on space and channel and a global context extraction module to highlight more valuable information. To evaluate the performance of RCGA-Net, we apply it to different kinds of clinical and experimental MIS tasks to testify its generalization ability. Extensive experiments represent that our schema has taken the outperform or compatible results among the comparison methods group. Specifically, the numeric result of RCGA-Net on the pulmonary dataset has achieved a 99.12% optimum F1-score. © 2021 IEEE.

关键词： Diagnosis

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

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

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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.

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

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

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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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Lightdet: A Lightweight and Accurate Object Detection Network

Lightdet: A Lightweight and Accurate Object Detection Networ...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Qiankun Tang Jie Li Zhiping Shi Yu Hu Research Center for Intelligent Computing Systems State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing Advanced Innovation Center for Imaging Theory and Technology Capital Normal University

ISBN: (数字)9781509066315

ISBN: (纸本)9781509066322

The extensive computational burden limits the usage of accurate but complex object detectors in resource-bounded scenarios. In this paper, we present a lightweight object detector, named LightDet, to address this dilemma. We design a lightweight backbone that is able to capture rich low-level features by the proposed Detail-Preserving Module. To effectively aggregate bottom and top-down features, we introduce an efficient Feature-Preserving and Refinement Module. A lightweight prediction head is employed to further reduce the entire network complexity. Experimental results show that our LightDet achieves 75.5% mAP on PASCAL VOC 2007 at the speed of 250 FPS and 24.0% mAP on MS COCO dataset.

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