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Bi-Directional and Triangular Circulation Fusion Neural Networks for Small Object Detection

IEEE Transactions on Circuits and systems for Video technology 2024年第6期35卷 5140-5152页

作者： Li, Fangyu Duan, Junzhu Zhang, Qiyu Shan, Caifeng Han, Honggui the School of Information Science and Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System Engineering Research Center of Digital Community Ministry of Education Beijing Artificial Intelligence Institute Beijing University of Technology Beijing100124 China the State Key Laboratory for Novel Software Technology Nanjing University Nanjing210023 China the School of Intelligence Science and Technology Nanjing University Suzhou215163 China

Deep learning-driven object detection models are capable of accurately identifying and localizing objects. However, small objects contain limited information relative to global features, resulting in the fact that detection models often do not learn small object features adequately. To enhance the precision in detecting small objects, we propose a bi-directional and triangular circulation fusion neural network (BTFN). First, to selectively strengthen the position features of small objects, we propose a feature circulation extraction module composed of a bi-directional triangular densely nested convolutional network (BTF), thus achieving repetitive multi-layer feature fusion. Second, to fill up the semantic gaps between different scales of features, we design a mixed dual attention module (MDA) in the bi-directional triangular densely nested network. Third, to mitigate the lost information in the neural networks with deep layers as well as improve the inference time, we design a re-parameterization bi-directional composite feature fusion module (Rep-BFM) that fuses the features of multiple scales. The proposed model is evaluated extensively on the MS COCO, Tsinghua-Tencent 100k, and Haier dismantled parts of used home appliances datasets. The experiment results show that the proposed model improves the AP on MS COCO by 4%, especially the APS of small objects is improved by 7.7% compared with SOTA models. © 2024 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Domestic appliances

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A healable, mechanically robust and ultrastretchable ionic conductive elastomer for durably wearable sensor

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Nano Research 2024年第4期17卷 3369-3378页

作者： Guoxian Zhang Chunmei Li JiaoJun Tan Mingqi Wang Yafeng Ren Feijie Ge Qiuyu Zhang Key Laboratory of Special Functional and Smart Polymer Materials of Ministry of Industry and Information Technology School of Chemistry and Chemical EngineeringNorthwestern Polytechnical UniversityXi'an 710072China College of Bioresources Chemical and Materials Engineering National Demonstration Center for Experimental Light Chemistry Engineering EducationShaanxi University of Science&TechnologyXi’an 710021China

The ionic conductive elastomers show great promise in multifunctional wearable electronics,but they currently suffer from liquid leakage/evaporation or mechanical *** ionic conductive elastomers integrating non-volatility,mechanical robustness,superior ionic conductivity,and ultra-stretchability remains urgent and ***,we developed a healable,robust,and conductive elastomer via impregnating free ionic liquids(ILs)into the ILs-multigrafted poly(urethane-urea)(PUU)elastomer networks.A crucial strategy in the molecular design is that imidazolium cations are largely introduced by double-modification of PUU and centipede-like structures are obtained,which can lock the impregnated ILs through strong ionic *** this system,the PUU matrix contributes outstanding mechanical properties,while the hydrogen bonds and ionic interactions endow the elastomer with self-healing ability,conductivity,as well as non-volatility and *** fabricated ionic conductive elastomers show good conductivity(3.8×10^(-6) S·cm^(-1)),high mechanical properties,including tensile stress(4.64 MPa),elongation(1470%),and excellent healing ability(repairing efficiency of 90%after healing at room temperature for 12 h).Significantly,the conductive elastomers have excellent antifatigue properties,and demonstrate a highly reproducible response after 1000 uninterrupted extension-release *** work provides a promising strategy to prepare ionic conductive elastomers with excellent mechanical properties and stable sensing capacity,and further promote the development of mechanically adaptable intelligent sensors.

关键词： ionic conductive elastomers poly(urethane-urea)(PUU) ionic interactions centipede-like self-healing

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Realizing Plain Optimization of the Thermoelectric Properties in BiCuSeO Oxide via Self-Substitution-Induced Lattice Dislocations

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Research 2023年第4期2023卷 755-764页

作者： Rui Xu Zhiwei Chen Qizhu Li Xiaoyu Yang Han Wan Mengruizhe Kong Wei Bai Nengyuan Zhu Ruohan Wang Jiming Song Zhou Li Chong Xiao Binghui Ge Information Materials and Intelligent Sensing Laboratory of Anhui Province Key Laboratory of Structure and Functional Regulation of Hybrid Materials of Ministry of EducationInstitutes of Physical Science and Information Technology and School of Materials Science and EngineeringAnhui UniversityHefei 230601China Institute of Energy Hefei Comprehensive National Science CenterHefei 230031China School of Materials Science and Engineering Tongji UniversityShanghai 201804China Hefei National Laboratory for Physical Sciences at the Microscale CAS Center for Excellence in NanoscienceUniversity of Science and Technology of ChinaHefei 230026China

Seeking new strategies to tune the intrinsic defect and optimize the thermoelectric performance via no or less use of external doped elements(i.e.,plain optimization)is an important method to realize the sustainable development of thermoelectric ***,creating dislocation defects in oxide systems is quite challenging because the rigid and stiff ionic/covalent bonds can hardly tolerate the large strain energy associated with ***,taking BiCuSe_(O) oxide as an example,the present work reports a successful construction of dense lattice dislocations in BiCuSe_(O) by self-doping of Se at the O site(i.e.,Se_(O) self-substitution),and achieves plain optimization of the thermoelectric properties with only external Pb *** to the self-substitution-induced large lattice distortion and the potential reinforcement effect by Pb doping,high-density(about 3.0×10^(14 )m^(−2))dislocations form in the grains,which enhances the scattering strength of mid-frequency phonon and results in a substantial low lattice thermal conductivity of 0.38 W m^(−1) K^(−1) at 823 K in Pb-doped BiCuSe_(O).Meanwhile,PbBi doping and Cu vacancy markedly improve the electrical conductivity while maintaining a competitively high Seebeck coefficient,thereby contributing to a highest power factor of 942μW m^(−1) K^(−2).Finally,a remarkably enhanced zT value of 1.32 is obtained at 823 K in Bi_(0.94)Pb_(0.06)Cu_(0.97)Se_(1.05)O_(0.95) with almost compositional *** high-density dislocation structure reported in this work will also provide a good inspiration for the design and construction of dislocations in other oxide systems.

关键词： plain doping dislocation

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Multi-source information Fusion based Motor Fault Diagnosis via Deep Discriminative Residual Adaptation

Multi-source Information Fusion based Motor Fault Diagnosis ...

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2024 China Automation Congress, CAC 2024

作者： Qiao, Xiangbo Zhang, Yong Cui, Xiaopeng Zhou, Wei Lu, Shaowu Yan, Baokang School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China National Key Laboratory of Electromagnetic Energy Naval University of Engineering Wuhan China

ISBN: (纸本)9798350368604

Asynchronous motors play a key role in industrial equipment. To cope with the challenge of incomplete fault information due to a single signal, and the problem of missing target domain labels. this paper proposes a method that combines multi-source information fusion with an improved domain adaptation approach. First, an autoencoder is used to extract features from the collected vibration, current and temperature signals. The extracted features are concatenated and fused at the channel level. Then, a deep feature extraction network is designed by combining efficient channel attention and deep residual network, which can accurately and efficiently extract deep features from multi-source information. Finally, an improved domain adaptation mechanism is proposed, which significantly enhances the learning of discriminative features between two different domains. In addition, by incorporating the I-Softmax loss, the constructed Deep Discriminative Residual Adaptive Network exhibits stronger classification capabilities. The superiority and feasibility of the proposed method is verified by comparing several methods under the sample of asynchronous motor without labeling the target domain. © 2024 IEEE.

关键词： information fusion

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Fast Hybrid Far/Near-Field Beam Training For Extremely Large-Scale Millimeter Wave/Terahertz systems

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IEEE Transactions on Communications 2024年第6期73卷 3956-3970页

作者： Wang, Hongwei Fang, Jun Duan, Huiping Li, Hongbin University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications Chengdu611731 China University of Electronic Science and Technology of China School of Information and Communications Engineering Chengdu611731 China Stevens Institute of Technology Department of Electrical and Computer Engineering HobokenNJ07030 United States

In this paper, we consider the problem of downlink beam training for extremely large-scale millimeter wave (mmWave)/Terahertz (THz) systems, where the far-field assumption which treats wavefronts as planar waves may not hold valid. For such hybrid far/near-field channels, beam training needs to identify the best beam alignment on a two-dimensional angle-range domain. An exhaustive search scheme sequentially scanning the entire angle-range space incurs a high training overhead. To address this issue, in this paper, we propose an efficient hybrid far/near-field beam training method. By utilizing the approximate orthogonality of near-field steering vectors of the same effective distance, we devise a multi-directional beam training sequence which can more efficiently scan the entire angle-range space. Based on the devised beam training sequence, we develop a simple estimation method at the receiver that can simultaneously identify the angle and the range associated with the dominant path. Simulation results show that the proposed method achieves better performance than the exhaustive search scheme, while with a much lower overhead cost. The proposed method also presents a clear advantage over other existing state-of-the-art hybrid far/near-field beam training methods in terms of performance and generality. © 1972-2012 IEEE.

关键词： Wavefronts

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Digital Twin-assisted Gearbox Fault Diagnosis Framework using Hybrid Adversarial Domain Discriminative Networks

Digital Twin-assisted Gearbox Fault Diagnosis Framework usin...

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2024 China Automation Congress, CAC 2024

作者： Ge, Yukang Zhang, Yong Liao, Tao Ping, Zuowei Chen, Jianliang Duan, Yaqiong School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China National Key Laboratory of Electromagnetic Energy Naval University of Engineering Wuhan China

ISBN: (纸本)9798350368604

In industrial applications, fault diagnosis of gearboxes is critical for ensuring the reliability and safe operation of machinery and equipment. However, data-driven fault diagnosis techniques rely heavily on high-quality labeled data for training, which is often difficult to obtain in real industrial scenarios. To address this challenge, this paper presents a digital twin fault diagnosis framework. First, the digital twin technique is utilized to build a virtual model of a gearbox that generates sufficient labeled fault data. Second, we develop a hybrid adversarial domain discriminative network, which incorporates a spatial channel reconstruction convolution module instead of a conventional residual network to enhance the model’s feature extraction capabilities. Additionally, we propose a dynamic weighted joint distribution adaptation method to improve domain confusion capability, minimizing the granularity of features between the two types of data. Finally, the effectiveness and reliability of the proposed method are validated through experiments. © 2024 IEEE.

关键词： Gears

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Polarization-induced photocurrent switching effect in heterojunction photodiodes

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Nano Research 2023年第4期16卷 5503-5510页

作者： Dingbo Chen Yu-Chang Chen Guang Zeng Yu-Chun Li Xiao-Xi Li Dong Li Chao Shen Nan Chi Boon S.Ooi David Wei Zhang Hong-Liang Lu State Key Laboratory of ASIC and System Shanghai Institute of Intelligent Electronics&SystemsSchool of MicroelectronicsFudan UniversityShanghai 200433China Key Laboratory for Information Science of Electromagnetic Waves Department of Communication Science and EngineeringFudan UniversityShanghai 200433China Photonics Laboratory Division of ComputerElectricaland Mathematical Sciences and EngineeringKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia

The unipolar photocurrent in conventional photodiodes(PDs)based on photovoltaic effect limits the output modes and potential versatility of these devices in *** photodiodes with photocurrent switching are emerging as a promising solution for obtaining photoelectric devices with unique and attractive functions,such as optical logic ***,we design an all-solid-state chip-scale ultraviolet(UV)PD based on a hybrid GaN heterojunction with engineered bipolar polarized electric *** introducing the polarization-induced photocurrent switching effect,the photocurrent direction can be switched in response to the wavelength of incident light at 0 V *** particular,the photocurrent direction exhibits negative when the irradiation wavelength is less than 315 nm,but positive when the wavelength is longer than 315 *** device shows a responsivity of up to−6.7 mA/W at 300 nm and 5.3 mA/W at 340 nm,*** particular,three special logic gates in response to different dual UV light inputs are demonstrated via a single bipolar PD,which may be beneficial for future multifunctional UV photonic integrated devices and systems.

关键词： GaN heterostructure ultraviolet(UV)photodiodes bipolar photocurrent optical logic device

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Multiple model PHD filter for tracking sharply maneuvering targets using recursive RANSAC based adaptive birth estimation

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Journal of systems engineering and Electronics 2024年第3期35卷 780-792页

作者： DING Changwen ZHOU Di ZOU Xinguang DU Runle LIU Jiaqi School of Astronautics Harbin Institute of TechnologyHarbin 150001China School of Electronics and Information Engineering Harbin Institute of TechnologyHarbin 150001China National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing 100076China

An algorithm to track multiple sharply maneuvering targets without prior knowledge about new target birth is proposed. These targets are capable of achieving sharp maneuvers within a short period of time, such as drones and agile *** probability hypothesis density (PHD) filter, which propagates only the first-order statistical moment of the full target posterior, has been shown to be a computationally efficient solution to multitarget tracking problems. However, the standard PHD filter operates on the single dynamic model and requires prior information about target birth distribution, which leads to many limitations in terms of practical applications. In this paper,we introduce a nonzero mean, white noise turn rate dynamic model and generalize jump Markov systems to multitarget case to accommodate sharply maneuvering dynamics. Moreover, to adaptively estimate newborn targets’information, a measurement-driven method based on the recursive random sampling consensus (RANSAC) algorithm is proposed. Simulation results demonstrate that the proposed method achieves significant improvement in tracking multiple sharply maneuvering targets with adaptive birth estimation.

关键词： multitarget tracking probability hypothesis density(PHD)filter sharply maneuvering targets multiple model adaptive birth intensity estimation

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C1M2:a universal algorithm for 3D instance segmentation,annotation,and quantification of irregular cells

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science China(Life sciences) 2023年第10期66卷 2415-2428页

作者： Hao Zheng Songlin Huang Jing Zhang Ren Zhang Jialu Wang Jing Yuan Anan Li Xin Yang Zhihong Zhang Britton Chance Center and MOE Key Laboratory for Biomedical Photonics Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and TechnologyWuhan 430074China Key Laboratory of Biomedical Engineering of Hainan Province School of Biomedical EngineeringHainan UniversityHaikou 570228China School of Electronic Information and Communications Huazhong University of Science and TechnologyWuhan 430074China

Cell instance segmentation is a fundamental task for many biological applications,especially for packed cells in three-dimensional(3D)microscope images that can fully display cellular *** processing algorithms based on neural networks and feature engineering have enabled great progress in two-dimensional(2D)instance ***,current methods cannot achieve high segmentation accuracy for irregular cells in 3D *** this study,we introduce a universal,morphology-based 3D instance segmentation algorithm called Crop Once Merge Twice(C1M2),which can segment cells from a wide range of image types and does not require nucleus images.C1M2 can be extended to quantify the fluorescence intensity of fluorescent proteins and antibodies and automatically annotate their expression levels in individual *** results suggest that C1M2 can serve as a tissue cytometry for 3D histopathological assays by quantifying fluorescence intensity with spatial localization and morphological information.

关键词： 3D instance segmentation irregular cells fluorescence images neural networks fluorescence intensity tissue cytometry

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Spatial and Temporal Distribution of Metal Elements in the Rivers of Northern Jiangsu Province

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Journal of Ocean University of China 2025年第1期24卷 157-168页

作者： YUAN Liping LIU Qian JIAN Huimin MI Tiezhu YANG Fuxia YAO Qingzhen Frontiers Science Center for Deep Ocean Multispheres and Earth System and Key Laboratory of Marine Chemistry Theory and TechnologyMinistry of EducationOcean University of ChinaQingdao 266100China Laboratory of Marine Ecology and Environmental Science Qingdao National Laboratory for Marine Science and TechnologyQingdao 266071China College of Environmental Science and Engineering Ocean University of ChinaQingdao 266100China Key Laboratory of Land and Sea Ecological Governance and Systematic Regulation of the Ministry of Ecology and Environment Shandong Academy for Environmental PlanningJinan 250101China

The concentrations of V,Cr,Mn,Fe,Co,Ni,Cu,Zn,As,Mo,Cd,and Pb were determined in Doulonggang River,Xinyanggang River,Huangshagang River,Sheyanghe River,Guangaizongqu River,and Linhonghe River at the North of Jiangsu Province in *** annual average concentrations of V,Cr,Mn,Fe,Co,Ni,Cu,Zn,As,Mo,Cd and Pb in the six rivers were 2.20,1.22,4.53,21.9,0.13,2.79,1.77,4.00,2.97,3.87,0.01,0.19μg L^(-1)*** highest concentration of most trace metals were found in Guangaizongqu River and Linhonghe River,and the lowest concentration were found in Xinyanggang River and Huangshagang *** principal component analysis(PCA)resulted of two factors together explained 91.2%of the variance with>1initial eigenvalue,indicating that both natural and anthropogenic activities were contributing factors as the source of metal abundance in rivers of northern Jiangsu *** first major component represented the influence of anthropogenic activities,including industry and agriculture,with a contribution rate of 54.1%,affected Cr,Fe,Cu,Zn,Mo,Cd and *** second(such as V,Mn,Co,Ni,As)was a mixed source,including the natural processes such as precipitation,erosion and weathering and anthropogenic action like industry and agriculture,with a contribution rate of 37.1%.Seasonal variations in trace metal concentrations were influenced by temperature,salinity,water discharge,and input of external *** highest concentrations were found in wet season and were strongly influenced by rainfall and seasonal industrial and agricultural activities.

关键词： trace metal distribution rivers northern Jiangsu Province

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