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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Zhao, Chenyang Hu, Chuanfei Shao, Hang Wang, Zhe Wang, Yongxiong Southeast University The College of Software Engineering Nanjing China University of Shanghai for Science and Technology School of Optical-Electrical and Computer Engineering Shanghai China Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing China

ISBN: (纸本)9781728163277

An automatic vision-based sewer inspection plays a key role of sewage system in a modern city. Recent advances focus on utilizing deep learning model to realize the sewer inspection system, benefiting from the capability of data-driven feature representation. However, the inherent uncertainty of sewer defects is ignored, resulting in the missed detection of serious unknown sewer defect categories. In this paper, we propose a trustworthy multi-label sewer defect classification (TMSDC) method, which can quantify the uncertainty of sewer defect prediction via evidential deep learning. Meanwhile, a novel expert base rate assignment (EBRA) is proposed to introduce the expert knowledge for describing reliable evidences in practical situations. Experimental results demonstrate the effectiveness of TMSDC and the superior capability of uncertainty estimation is achieved on the latest public benchmark. © 2023 IEEE.

关键词： Defects

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Broadband spin and angle co‑multiplexed waveguide‑based metasurface for six‑channel crosstalk‑free holographic projection

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eLight 2024年第1期4卷 223-237页

作者： Zeyang Liu Hao Gao Taigao Ma Vishva Ray Niu Liu Xinliang Zhang L.Jay Guo Cheng Zhang School of Optical and Electronic Information Huazhong University of Science and TechnologyWuhan 430074China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan 430074China Department of Physics University of MichiganAnn ArborMI 48109USA Lurie Nanofabrication Facility Department of Electrical Engineering and Computer ScienceUniversity of MichiganAnn ArborMI 48109USA Department of Electrical Engineering and Computer Science University of MichiganAnn ArborMI 48109USA

Metasurface-based holograms,or metaholograms,offer unique advantages including enhanced imaging quality,expanded field of view,compact system size,and broad operational ***-channel metaholograms,capable of switching between multiple projected images based on the properties of illuminating light such as state of polarization and angle of incidence,have emerged as a promising solution for realizing switchable and dynamic holographic ***,existing designs typically grapple with challenges such as limited multiplexing channels and unwanted crosstalk,which severely constrain their practical ***,we present a new type of waveguidebased multi-channel metaholograms,which support six independent and fully crosstalk-free holographic display channels,simultaneously multiplexed by the spin and angle of guided incident light within the glass *** employ a k-space translation strategy that allows each of the six distinct target images to be selectively translated from evanescent-wave region to the center of propagation-wave region and projected into free space without crosstalk,when the metahologram is under illumination of a guided light with specific spin and azimuthal *** addition,by tailoring the encoded target images,we implement a three-channel polarization-independent metahologram and a two-channel full-color(RGB)***,the number of multiplexing channels can be further increased by expanding the k-space’s central-period region or combing the k-space translation strategy with other multiplexing techniques such as orbital angular momentum *** work provides a novel approach towards realization of high-performance and compact holographic optical elements with substantial information capacity,opening avenues for applications in AR/VR displays,image encryption,and information storage.

关键词： Metasurface Multi-channel metahologram Color metahologram Waveguide display

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Edge-Driven Industrial Computing Power Networks: Digital Twin-Empowered Service Provisioning by Hybrid Soft Actor-Critic

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IEEE Transactions on Vehicular Technology 2025年第5期74卷 8095-8109页

作者： Zhang, Long Song, Deng-Ao Zhang, Hongliang Tian, Ni Zhuang, Zirui Niyato, Dusit Han, Zhu Hebei University of Engineering School of Information and Electrical Engineering Handan056038 China Peking University State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Beijing100871 China Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing100876 China Nanyang Technological University College of Computing and Data Science 639798 Singapore University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

With the proliferation of data-intensive industrial applications, the collaboration of computing powers among standalone edge servers is vital to provision such services for smart devices. In this paper, we propose an edge-driven industrial computing power network (CPN) by orchestrating the computing and network resources of edge servers through the centralized resource scheduling and decentralized task computing. However, efficient task offloading and collaborative processing is challenging, which requires higher degrees of network automation and intelligence. Therefore, we incorporate digital twins (DTs) into the edge-driven CPN architecture, where the DTs are created as the digital replicas to assist both the computation offloading and collaborative processing. A joint optimization problem of the computing power assignment, service association, task partition, and transmit power control is formulated for maximizing the system average weighted utility. Due to the temporal-spatial variability of tasks and the resulted dynamic environment, we transform the original problem as a Markov decision process aiming at maximizing the long-term average weighted utility. To efficiently handle the high-dimensional discrete-continuous action space, a hybrid soft actor-critic based deep reinforcement learning algorithm is developed for optimizing the joint design. Simulation results validate the superiority of our proposed algorithm over the benchmarks, showing the significant gains obtained by integrating DTs into the edge-driven CPN. © 1967-2012 IEEE.

关键词： Markov processes

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Wavelet-Based Mamba with Fourier Adjustment for Low-Light Image Enhancement 17th

Wavelet-Based Mamba with Fourier Adjustment for Low-Light ...

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17th Asian Conference on computer Vision, ACCV 2024

作者： Tan, Junhao Pei, Songwen Qin, Wei Fu, Bo Li, Ximing Huang, Libo School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China School of Computer Science and Artificial Intelligence Liaoning Normal University Liaoning116081 China College of Computer Science and Technology Jilin University Jilin134000 China School of Computer National University of Dense Technology Changsha410073 China

ISBN: (纸本)9789819609109

Frequency information (e.g., Discrete Wavelet Transform and Fast Fourier Transform) has been widely applied to solve the issue of Low-Light Image Enhancement (LLIE). However, existing frequency-based models primarily operate in the simple wavelet or Fourier space of images, which lacks utilization of valid global and local information in each space. We found that wavelet frequency information is more sensitive to global brightness due to its low-frequency component while Fourier frequency information is more sensitive to local details due to its phase component. In order to achieve superior preliminary brightness enhancement by optimally integrating spatial channel information with low-frequency components in the wavelet transform, we introduce channel-wise Mamba, which compensates for the long-range dependencies of CNNs and has lower complexity compared to Diffusion and Transformer models. So in this work, we propose a novel Wavelet-based Mamba with Fourier Adjustment model called WalMaFa, consisting of a Wavelet-based Mamba Block (WMB) and a Fast Fourier Adjustment Block (FFAB). We employ an Encoder-Latent-Decoder structure to accomplish the end-to-end transformation. Specifically, WMB is adopted in the Encoder and Decoder to enhance global brightness while FFAB is adopted in the Latent to fine-tune local texture details and alleviate ambiguity. Extensive experiments demonstrate that our proposed WalMaFa achieves state-of-the-art performance with fewer computational resources and faster speed. Code is now available at: https://***/mcpaulgeorge/WalMaFa. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Image enhancement

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Histogram Matching-Based Reversible Data Hiding for Intelligent Transportation Applications

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IEEE Internet of Things Journal 2025年

作者： Zhang, Kexin Yao, Heng Yang, Xin Qin, Chuan University of Shanghai for Science and Technology School of Optical-Electrical and Computer Engineering Shanghai200093 China

In today's intelligent transportation systems, the effectiveness of image-based analysis relies heavily on image quality. To enhance images while preserving reversibility, this paper proposes a histogram matching-based reversible data hiding (HMRDH) method. The proposed approach ensures high embedding capacity by incorporating histogram shifting from reversible data hiding with contrast enhancement (RDHCE). Unlike traditional RDHCE methods that are limited to achieving histogram equalization, our method constrains the sequence of bin adjustments to achieve flexible histogram matching. The algorithm first evaluates bin heights to assign roles, then iteratively selects and adjusts corresponding bins while embedding *** prevent deviation from the target histogram, this method calculates the root mean square error after each iteration to ensure that the adjustment is retained only if it improves the matching accuracy. When necessary, the original image and embedded information can be fully recovered. Extensive experiments demonstrate the superiority of the proposed method in visual quality, embedding capacity, and adaptability. © 2025 IEEE.

关键词： Contrast enhancement Histogram matching Intelligent transportation system (ITS) Internet of things (IoT) Reversible data hiding

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HFGGRFN: High-frequency guided group recurrent feedback network for hyperspectral image fusion

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Optics and Laser Technology 2025年 188卷

作者： Liu, Cong Mei, Jing School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China

Obtaining a high-resolution hyperspectral image (HR-HSI) by fusing a low-resolution hyperspectral image (LR-HSI) with a high-resolution multispectral image (HR-MSI) is a highly effective approach, and numerous fusion methods have achieved remarkable success in recent years. However, most existing fusion methods take the LR-HSI and HR-MSI as two entire inputs, which hamper the full capture of spectral information due to the extensive number of spectral bands. Furthermore, these methods fail to fully exploit the spatial high-frequency information by relying solely on the HR-MSI. In this paper, we propose a High-Frequency Guided Group Recurrent Feedback Network (HFGGRFN) for hyperspectral image fusion to enhance the accuracy of HSI fusion. The proposed HFGGRFN comprises three key components. Firstly, a High-Frequency Guided Grouping Input (HFGGI) module is designed to divide the LR-HSI, HR-MSI, and high-frequency features derived from the HR-MSI into several groups, thereby effectively preserving spectral correlations. Secondly, a Feature Recurrent Feedback Fusion (FRFF) module is developed, which not only fully integrates the LR-HSI and HR-MSI within each group but also comprehensively captures spectral correlations among adjacent groups. Thirdly, a High-Frequency Information Injection (HFII) module is incorporated to inject high-frequency information obtained from the HR-MSI into the network, thereby highlighting spatial details. Experimental results demonstrate the superiority of the proposed method over state-of-the-art approaches in six commonly used metrics and visual assessments, underscoring its effectiveness in enhancing hyperspectral image fusion accuracy. © 2025 Elsevier Ltd

关键词： Image fusion

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Learning of Molecular Graphs in Toxicity Prediction 23

Learning of Molecular Graphs in Toxicity Prediction

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23rd International Conference on Machine Learning and Cybernetics, ICMLC 2024

作者： Huang, Yuting Peng, Dunlu Wang, Debby D. School of Science and Technology Hong Kong Metropolitan University Kowloon Ho Man Tin Hong Kong School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai20093 China

ISBN: (纸本)9798331528041

In-silico toxicity prediction plays a key role in the health industry and research. Machine learning has been widely rewarded for its high efficiency in this field, but the methods are mostly expertise driven and with limited growth. After mitigating many practical problems smartly, deep learning has also been entrusted with high expectations in toxicity prediction. In this work, we attempted to predict compound toxicity by leveraging a graph representation of the compounds and a neat graph-learning framework. Key atomic and bond features were captured by the graph representations, and different graph-learning techniques in the framework were investigated. As evaluated on the Tox21 data, the graph-learning framework possesses a good potential in attaining state-of-the-art performances and handling imbalanced data in toxicity prediction tasks. © 2024 IEEE.

关键词： Adversarial machine learning

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Mid-infrared tunable interband cascade laser employing double-trench waveguide structure with a tuning range of 118 nm 21

Mid-infrared tunable interband cascade laser employing doubl...

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21st International Conference on optical Communications and Networks, ICOCN 2023

作者： Wang, Zhanyi Gong, Jingli Yang, Rui Q. He, Jian-Jun College of Optical Science and Engineering Zhejiang University State Key Laboratory of Modern Optical Instrumentation Hangzhou310027 China The University of Oklahoma School of Electrical and Computer Engineering NormanOK73019 United States

We present a widely tunable single-mode interband cascade laser (ICL) emitting at 3.3 μm based on the V-coupled cavity employing a double-trench structure, with aside-mode suppression ratio of up to 36 dB. © 202... 详细信息

ISBN: (纸本)9798350343502

关键词： Infrared devices

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High performance“non-local”generic face reconstruction model using the lightweight Speckle-Transformer(SpT)UNet

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Opto-Electronic Advances 2023年第2期6卷 1-9页

作者： Yangyundou Wang Hao Wang Min Gu Institute of Photonic Chips University of Shanghai for Science and TechnologyShanghai 200093China Centre for Artificial-Intelligence Nanophotonics School of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and TechnologyShanghai 200093China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China

Significant progress has been made in computational imaging(CI),in which deep convolutional neural networks(CNNs)have demonstrated that sparse speckle patterns can be ***,due to the limited“local”kernel size of the convolutional operator,for the spatially dense patterns,such as the generic face images,the performance of CNNs is ***,we propose a“non-local”model,termed the Speckle-Transformer(SpT)UNet,for speckle feature extraction of generic face *** is worth noting that the lightweight SpT UNet reveals a high efficiency and strong comparative performance with Pearson Correlation Coefficient(PCC),and structural similarity measure(SSIM)exceeding 0.989,and 0.950,respectively.

关键词： speckle reconstruction non-local model generic face images lightweight network

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Disturbance Rejection Target Tracking Control for Snake Robots in the Presence of Obstacles 3

Disturbance Rejection Target Tracking Control for Snake Robo...

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3rd IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2024

作者： Li, Ningwei Chu, Yiming Ren, Shanjun Wang, Chaoli Wang, Gang Li, Peng Institude of Machine Intelligence University of Shanghai for Science and Technology Shanghai China School of Optical Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China

ISBN: (纸本)9798331540319

In this paper, a collision-free target tracking control approach utilizing guided vector field guidance is proposed. In particular, a synthesized vector field is designed to direct the snake robot toward the target while simultaneously navigating around multiple obstacles. In addition, a saturated guidance law is designed to compute a reference angular velocity to prevent damage to the robot joints. A dynamics control law is designed based on a reduced-order structure-modified expansion state observer to compensate for external disturbances and realize the robust target tracking and tracing control of the snake robot. Simulation results show the effectiveness of the proposed guidance and control method. © 2024 IEEE.

关键词： Disturbance rejection

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