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A Novel Multi-Stream Fusion Network for Underwater image Enhancement

China communications 2024年第2期21卷 166-182页

作者： Guijin Tang Lian Duan Haitao Zhao Feng Liu Jiangsu key laboratory of image processing and image communication Nanjing University of Posts and TelecommunicationsNanjing 210003China Jiangsu key laboratory of Wireless communications Nanjing University of Posts and TelecommunicationsNanjing 210003China

Due to the selective absorption of light and the existence of a large number of floating media in sea water, underwater images often suffer from color casts and detail blurs. It is therefore necessary to perform color correction and detail restoration. However,the existing enhancement algorithms cannot achieve the desired results. In order to solve the above problems, this paper proposes a multi-stream feature fusion network. First, an underwater image is preprocessed to obtain potential information from the illumination stream, color stream and structure stream by histogram equalization with contrast limitation, gamma correction and white balance, respectively. Next, these three streams and the original raw stream are sent to the residual blocks to extract the features. The features will be subsequently fused. It can enhance feature representation in underwater images. In the meantime, a composite loss function including three terms is used to ensure the quality of the enhanced image from the three aspects of color balance, structure preservation and image smoothness. Therefore, the enhanced image is more in line with human visual ***, the effectiveness of the proposed method is verified by comparison experiments with many stateof-the-art underwater image enhancement algorithms. Experimental results show that the proposed method provides superior results over them in terms of MSE,PSNR, SSIM, UIQM and UCIQE, and the enhanced images are more similar to their ground truth images.

关键词： image enhancement multi-stream fusion underwater image

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Revolutionary entrapment model of uniformly distributed swarm robots in morphogenetic formation

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Defence Technology（防务技术） 2024年第1期31卷 496-509页

作者： Chen Wang Zhaohui Shi Minqiang Gu Weicheng Luo Xiaomin Zhu Zhun Fan Shantou University ShantouGuangdongChina National University of Defense Technology ChangshaChina key lab of Digital Signal and image processing of Guangdong Province China

This study proposes a method for uniformly revolving swarm robots to entrap multiple targets,which is based on a gene regulatory network,an adaptive decision mechanism,and an improved *** the gene regulatory network method,the robots can generate entrapping patterns according to the environmental input,including the positions of the targets and ***,an adaptive decision mechanism is proposed,allowing each robot to choose the most well-adapted capture point on the pattern,based on its *** robots employ an improved Vicsek-model to maneuver to the planned capture point smoothly,without colliding with other robots or *** proposed decision mechanism,combined with the improved Vicsek-model,can form a uniform entrapment shape and create a revolving effect around targets while entrapping *** study also enables swarm robots,with an adaptive pattern formation,to entrap multiple targets in complex *** robots can be deployed in the military field of unmanned aerial vehicles’(UAVs)entrapping multiple *** experiments demonstrate the feasibility and superiority of the proposed gene regulatory network method.

关键词： Swarm intelligence Revolutionary entrapment Flocking Robots Gene regulatory network Vicsek-model Entrapping multiple targets

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Analysis of phase preservation and interferometric offset test in sparse SAR imaging

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Science China(Information Sciences) 2024年第2期67卷 219-231页

作者： Zhongqiu XU Bingchen ZHANG Guangzuo LI Xueli ZHAN Yanfei BAO Yirong WU key laboratory of Spatial Information processing and Application System Technology Chinese Academy of Sciences Aerospace Information Research Institute Chinese Academy of Sciences School of Electronic Electrical and Communication EngineeringUniversity of Chinese Academy of Sciences PLA Academy of Military Sciences

Sparse synthetic aperture radar(SAR) imaging has emerged as a reliable microwave imaging scheme in the recent decade and excels in down-sampling reconstruction and full-sampling performance improvements such as noise, sidelobe, speckle, and ambiguity suppression. To utilize complex image products of sparse reconstruction for improvement in polarimetric, interferometric, and tomographic SAR imaging, it is necessary to evaluate the phase preservation of sparse SAR imaging. In this study, we first introduce the general alternating direction method of multipliers(ADMM) as the universal framework for sparse reconstruction algorithms and adopt chirp scaling algorithm(CSA)-based azimuth-range decouple operators to avoid expensive data storage and processing. Further, we theoretically analyze the phase preservation of the sparse reconstruction algorithm through a comparison with the reconstruction results of CSA. Finally,we conduct the interferometric offset test on the sparse reconstruction results of simulated and real Gaofen-3(GF-3) SAR data, demonstrating the phase-preserving ability of sparse methods.

关键词： sparse SAR imaging phase preservation interferometric offset test general ADMM azimuth-range decouple

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Learnable digital signal processing:a new benchmark of linearity compensation for optical fiber communications

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Light(Science & Applications) 2024年第9期13卷 1931-1943页

作者： Zekun Niu Hang Yang Lyu Li Minghui Shi Guozhi Xu Weisheng Hu Lilin Yi State key lab of Advanced Optical communication Systems and Networks School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240PR China

The surge in interest regarding the next generation of optical fiber transmission has stimulated the development of digital signal processing(DSP)schemes that are highly cost-effective with both high performance and low *** benchmarks for nonlinear compensation methods,however,traditional DSP designed with block-by-block modules for linear compensations,could exhibit residual linear effects after compensation,limiting the nonlinear compensation *** we propose a high-efficient design thought for DSP based on the learnable perspectivity,called learnable DSP(LDSP).LDSP reuses the traditional DSP modules,regarding the whole DSP as a deep learning framework and optimizing the DSP parameters adaptively based on backpropagation algorithm from a global *** method not only establishes new standards in linear DSP performance but also serves as a critical benchmark for nonlinear DSP *** comparison to traditional DSP with hyperparameter optimization,a notable enhancement of approximately 1.21 dB in the Q factor for 400 Gb/s signal after 1600 km fiber transmission is experimentally demonstrated by combining LDSP and perturbation-based nonlinear compensation *** from the learnable model,LDSP can learn the best configuration adaptively with low complexity,reducing dependence on initial *** proposed approach implements a symbol-rate DSP with a small bit error rate(BER)cost in exchange for a 48%complexity reduction compared to the conventional 2 samples/symbol *** believe that LDSP represents a new and highly efficient paradigm for DSP design,which is poised to attract considerable attention across various domains of optical communications.

关键词： fiber signal optical

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Properties of focused Laguerre–Gaussian beam propagating in anisotropic ocean turbulence

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Chinese Physics B 2024年第2期33卷 386-393页

作者：王新光马洋斌袁邱杰陈伟王乐赵生妹 College of Science Nanjing University of Posts and TelecommunicationsNanjing 210003China Institute of Signal processing and Transmission Nanjing University of Posts and TelecommunicationsNanjing 210003China key lab of Broadband Wireless communication and Sensor Network Technology(Ministry of Education) Nanjing University of Posts and TelecommunicationsNanjing 210003China National laboratory of Solid State Microstructures Nanjing UniversityNanjing 210093China

We analyze the properties of a focused Laguerre–Gaussian(LG)beam propagating through anisotropic ocean turbulence based on the Huygens–Fresnel *** the Rytov approximation theory,we derive the analytical formula of the channel capacity of the focused LG beam in the anisotropic ocean turbulence,and analyze the relationship between the capacity and the light source parameters as well as the turbulent ocean *** is found that the focusing mirror can greatly enhance the channel capacity of the system at the geometric focal plane in oceanic *** results also demonstrate that the communication link can obtain high channel capacity by adopting longer beam wavelength,greater initial beam waist radius,and larger number of transmission ***,the capacity of the system increases with the decrease of the mean squared temperature dissipation rate,temperature-salinity contribution ratio and turbulence outer scale factor,and with the increase of the kinetic energy dissipation rate per unit mass of fluid,turbulence inner scale factor and anisotropy *** to a Hankel–Bessel beam with diffraction-free characteristics and unfocused LG beam,the focused LG beam shows superior anti-turbulence interference properties,which provide a theoretical reference for research and development of underwater optical communication links using focused LG beams.

关键词： vortex beam orbital angular momentum focusing mirror anisotropic turbulence

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Learning group interaction for sports video understanding from a perspective of athlete

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Frontiers of Computer Science 2024年第4期18卷 175-188页

作者： Rui HE Zehua FU Qingjie LIU Yunhong WANG Xunxun CHEN Intelligent Recognition and image processing(IRIP)lab School of Computer Science and EngineeringBeihang UniversityBeijing 100191China Hangzhou Innovation Institute Behang UniversityHangzhou 310051China National Computer Network Emergency Response Technical Team/Coordination Center of China(CNCERT or CNCERT/CC) Beijing 100029China

Learning activities interactions between small groups is a key step in understanding team sports *** research focusing on team sports videos can be strictly regarded from the perspective of the audience rather than the *** team sports videos such as volleyball and basketball videos,there are plenty of intra-team and inter-team *** this paper,a new task named Group Scene Graph Generation is introduced to better understand intra-team relations and inter-team relations in sports *** tackle this problem,a novel Hierarchical Relation Network is *** all players in a video are finely divided into two teams,the feature of the two teams’activities and interactions will be enhanced by Graph Convolutional Networks,which are finally recognized to generate Group Scene *** evaluation,built on Volleyball dataset with additional 9660 team activity labels,a Volleyball+dataset is proposed.A baseline is set for better comparison and our experimental results demonstrate the effectiveness of our ***,the idea of our method can be directly utilized in another video-based task,Group Activity *** show the priority of our method and display the link between the two ***,from the athlete’s view,we elaborately present an interpretation that shows how to utilize Group Scene Graph to analyze teams’activities and provide professional gaming suggestions.

关键词： group scene graph group activity recognition scene graph generation graph convolutional network sports video understanding

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Generation of orbital angular momentum hologram using a modified U-net

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Chinese Physics B 2024年第3期33卷 401-407页

作者：郑志刚韩菲菲王乐赵生妹 Institute of Signal processing and Transmission Nanjing University of Posts and TelecommunicationsNanjing 210003China key laboratory of Broadband Wireless communication and Sensor Network Technology (Ministry of Education) Nanjing University of Posts and TelecommunicationsNanjing 210003China National laboratory of Solid State Microstructures Nanjing UniversityNanjing 210093China

Orbital angular momentum(OAM)holography has become a promising technique in information encryption,data storage and opto-electronic computing,owing to the infinite topological charge of one single OAM mode and the orthogonality of different OAM *** this paper,we propose a novel OAM hologram generation method based on a densely connected U-net(DCU),where the densely connected convolution blocks(DCB)replace the convolution blocks of the ***,the reconstruction process of the OAM hologram is integrated into DCU as its output layer,so as to eliminate the requirement to prepare training data for the OAM hologram,which is required by conventional neural networks through an iterative *** experimental and simulation results show that the OAM hologram can rapidly be generated with the well-trained DCU,and the reconstructed image's quality from the generated OAM hologram is significantly improved in comparison with those from the Gerchberg-Saxton generation method,the Gerchberg-Saxton based generation method and the U-net *** addition,a 10-bit OAM multiplexing hologram scheme is numerically demonstrated to have a high capacity with OAM hologram.

关键词： orbital angular momentum(OAM) holography OAM holography deep learning

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Exercise-induced adaptation of neurons in the vertebrate locomotor system

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Journal of Sport and Health Science 2024年第2期13卷 160-171页

作者： Yue Dai Yi Cheng Renkai Ge Ke Chen Liming Yang key lab of Adolescent Health Assessment and Exercise Intervention of Ministry of Education College of Physical Education and Health CareEast China Normal UniversityShanghai 200241China Shanghai key laboratory of Multidimensional Information processing School of Communication and Electronic EngineeringEast China Normal UniversityShanghai 200241China School of Physical Education and Health Care East China Jiaotong UniversityNanchang 330013China key laboratory of High Confidence Software Technologies of Ministry of Education School of Computer SciencePeking UniversityBeijing 100871China

Vertebrate neurons are highly dynamic cells that undergo several alterations in their functioning and physiologies in adaptation to various external *** particular,how these neurons respond to physical exercise has long been an area of active *** of the vertebrate locomotor system’s adaptability suggest multiple mechanisms are involved in the regulation of neuronal activity and properties during *** this brief review,we highlight recent results and insights from the field with a focus on the following mechanisms:(a)alterations in neuronal excitability during acute exercise;(b)alterations in neuronal excitability after chronic exercise;(c)exercise-induced changes in neuronal membrane properties via modulation of ion channel activity;(d)exercise-enhanced dendritic plasticity;and(e)exercise-induced alterations in neuronal gene expression and protein *** hope is to update the community with a cellular and molecular understanding of the recent mechanisms underlying the adaptability of the vertebrate locomotor system in response to both acute and chronic physical exercise.

关键词： Dendritic plasticity Excitability Exercise Ion channel modulation Neuron adaptation

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FIFAWC: a dataset with detailed annotation and rich semantics for group activity recognition

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Frontiers of Computer Science 2024年第06期18卷 186351-186351页

作者： PEI Duoxuan HUANG Di WANG Yunhong State key laboratory of Software Development Environment School of Computer Science and Engineering Beihang University Intelligent Recognition and image processing lab. School of Computer Science and Engineering Beihang University

In this letter, we propose the FIFAWC dataset for GAR, offering unique features compared to existing ones. FIFAWC is meticulously annotated with all included GAs per sample augmenting both practicality and challenge. ... 详细信息

关键词： Semantics

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RGB-guided hyperspectral image super-resolution with deep progressive learning

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CAAI Transactions on Intelligence Technology 2024年第3期9卷 679-694页

作者： Tao Zhang Ying Fu Liwei Huang Siyuan Li Shaodi You Chenggang Yan School of Computer Science and Technology Beijing Institute of TechnologyBeijingChina Satellite Information Intelligent processing and Application Research laboratory Beijing Institute of Remote SensingBeijingChina key laboratory of Spectral Imaging Technology Xi'an Institute of Optics and Precision Mechanics of Chinese Academy of SciencesXi'anChina Institute of Informatics University of AmsterdamAmsterdamNetherlands School of communication Engineering Hangzhou Dianzi UniversityHangzhouChina

Due to hardware limitations,existing hyperspectral(HS)camera often suffer from low spatial/temporal ***,it has been prevalent to super-resolve a low reso-lution(LR)HS image into a high resolution(HR)HS image with a HR RGB(or mul-tispectral)image *** approaches for this guided super-resolution task often model the intrinsic characteristic of the desired HR HS image using hand-crafted ***,researchers pay more attention to deep learning methods with direct supervised or unsupervised learning,which exploit deep prior only from training dataset or testing *** this article,an efficient convolutional neural network-based method is presented to progressively super-resolve HS image with RGB image ***-ically,a progressive HS image super-resolution network is proposed,which progressively super-resolve the LR HS image with pixel shuffled HR RGB image ***,the super-resolution network is progressively trained with supervised pre-training and un-supervised adaption,where supervised pre-training learns the general prior on training data and unsupervised adaptation generalises the general prior to specific prior for variant testing *** proposed method can effectively exploit prior from training dataset and testing HS and RGB images with spectral-spatial *** has a good general-isation capability,especially for blind HS image *** experimental results show that the proposed deep progressive learning method out-performs the existing state-of-the-art methods for HS image super-resolution in non-blind and blind cases.

关键词： computer vision deep neural networks image processing image resolution unsupervised learning

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