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Numerical simulation for the initial state of avalanche in polydisperse particle systems

Chinese Physics B 2024年第2期33卷 405-412页

作者：韩韧李亭迟志鹏杨晖李然 School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China

Numerical simulation is employed to investigate the initial state of avalanche in polydisperse particle *** and propagation processes are illustrated for pentadisperse and triadisperse particle systems,*** these processes,particles involved in the avalanche grow slowly in the early stage and explosively in the later stage,which is clearly different from the continuous and steady growth trend in the monodisperse *** examining the avalanche propagation,the number growth of particles involved in the avalanche and the slope of the number growth,the initial state can be divided into three stages:T1(nucleation stage),T2(propagation stage),T3(overall avalanche stage).We focus on the characteristics of the avalanche in the T2 stage,and find that propagation distances increase almost linearly in both axial and radial directions in polydisperse *** also consider the distribution characteristics of the average coordination number and average velocity for the moving *** results support that the polydisperse particle systems are more stable in the T2 stage.

关键词： avalanche initial state polydisperse particle systems propagation

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Multi-Modal Self-Supervised Learning AlgorithmBased Product Recommendation

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IEEE Transactions on Automation Science and engineering 2025年 22卷 15371-15380页

作者： Gao, Li Fan, Haiping Chen, Qingkui Yang, Heyu School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai China

With the rise of e-commerce, personalized recommendation algorithms have received much attention in recent years. Meanwhile, multimodal recommendation algorithms have become the next competitive track of personalized recommendation. The current mainstream recommendation algorithms (e.g., NeuMF, NGCF) rely too much on empirical data and do not effectively utilize multimodal information to model user preferences, while there is the problem of sparsity of user preference data. Secondly, they are still limited to using the same weights to fuse the item features of different modalities, and have the problem of inaccurate recommendation. For this reason, this paper proposes Multi-Modal Self-Supervised Learning Algorithm Based Product Recommendation (MMSLRec). (1) Data augmentation by self-supervised adversarial perturbation generation learning is performed to supplement the missing interaction information of tailed products to solve the common data sparsity problem in product recommendation. (2) A multimodal representation learning module is introduced to capture deep features in image and text modalities using AlexNet and Bert, respectively, in order to avoid the recommendation accuracy degradation problem caused by insufficient data feature learning. (3) Learning the user's perceived strength in different modalities, using the user co-occurrence matrix to fuse the features and make recommendations. Experiments on Amazon-Electronics, Amazon-Clothing, and Amazon-Baby, with different degrees of data sparsity verify the effectiveness of our MMSLRec in solving the data sparsity problem and the multimodal user preference modeling problem, and compared to the state-of-the-art baseline recommendation model on the three datasets, the Recall@20 improved by 9.26%, 3.11% and 2.92%, respectively. © 2004-2012 IEEE.

关键词： Self-supervised learning

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Real-time holographic camera for obtaining real 3D scene hologram

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Light(Science & Applications) 2025年第3期14卷 789-799页

作者： Zhao-Song Li Chao Liu Xiao-Wei Li Yi Zheng Qian Huang Yi-Wei Zheng Ye-Hao Hou Chen-Liang Chang Da-Wei Zhang Song-Lin Zhuang Di Wang Qiong-Hua Wang School of Instrumentation and Optoelectronic Engineering Beihang UniversityBeijing100191China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China

As a frontier technology,holography has important research values in fields such as bio-micrographic imaging,light feld modulation and data ***,the real-time acquisition of 3D scenes and high-fidelity reconstruction technology has not yet made a breakthrough,which has seriously hindered the development of ***,a novel holographic camera is proposed to solve the above inherent problems *** proposed holographic camera consists of the acquisition end and the calculation *** the acquisition end of the holographic camera,specially configured liquid materials and liquid lens structure based on voice-coil motor-driving are used to produce the liquid camera,so that the liquid camera can quickly capture the focus stack of the real 3D scene within 15 *** the calculation end,a new structured focus stack network(FS-Net)is designed for hologram *** training the FS-Net with the focus stack renderer and learnable Zernike phase,it enables hologram calculation within 13 *** the first device to achieve real-time incoherent acquisition and high-fidelity holographic reconstruction of a real 3D scene,our proposed holographic camera breaks technical bottlenecks of difficulty in acquiring the real 3D scene,low quality of the holographic reconstructed image,and incorrect defocus *** experimental results demonstrate the effectiveness of our holographic camera in the acquisition of focal plane information and hologram calculation of the real 3D *** proposed holographic camera opens up a new way for the application of holography in fields such as 3D display,light field modulation,and 3D measurement.

关键词： holographic camera feld modulation hologram calculation liquid lens structured focus stack network D scene reconstruction d scenes real time acquisition

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Orbit-Orbit Interaction in Spatiotemporal optical Vortex

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engineering 2025年第2期45卷 44-51页

作者： Jian Chen Jie Zhao Xi Shen Dewei Mo Cheng-Wei Qiu Qiwen Zhan School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China Shanghai Key Laboratory of Modern Optical System University of Shanghai for Science and TechnologyShanghai 200093China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore

While spin-orbit interaction has been extensively studied,few investigations have reported on the interaction between orbital angular momenta(OAMs).In this work,we study a new type of orbit-orbit coupling between the longitudinal OAM and the transverse OAM carried by a three-dimensional(3D)spatiotemporal optical vortex(STOV)in the process of tight *** 3D STOV possesses orthogonal OAMs in the x-y,t-x,and y-t planes,and is preconditioned to overcome the spatiotemporal astigmatism effect.x,y,and t are the axes in the spatiotemporal *** corresponding focused wavepacket is calculated by employing the Debye diffraction theory,showing that a phase singularity ring is generated by the interactions among the transverse and longitudinal vortices in the highly confined *** Fourier-transform decomposition of the Debye integral is employed to analyze the mechanism of the orbit-orbit *** is the first revelation of coupling between the longitudinal OAM and the transverse OAM,paving the way for potential applications in optical trapping,laser machining,nonlinear light-matter interactions,and more.

关键词： Spatiotemporal optical vortex Orbital angular momentum Momentum interaction Highly confined wavepacket Diffraction

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Liquid lens based holographic camera for real 3D scene hologram acquisition using end-to-end physical model-driven network

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Light(Science & Applications) 2024年第3期13卷 488-497页

作者： Di Wang Zhao-Song Li Yi Zheng You-Ran Zhao Chao Liu Jin-Bo Xu Yi-Wei Zheng Qian Huang Chen-Liang Chang Da-Wei Zhang Song-Lin Zhuang Qiong-Hua Wang School of Instrumentation and Optoelectronic Engineering Beihang UniversityBeijing 100191China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China

With the development of artificial intelligence,neural network provides unique opportunities for holography,such as high fidelity and dynamic *** to obtain real 3D scene and generate high fidelity hologram in real time is an urgent ***,we propose a liquid lens based holographic camera for real 3D scene hologram acquisition using an end-to-end physical model-driven network(EEPMD-Net).As the core component of the liquid camera,the first 10 mm large aperture electrowetting-based liquid lens is proposed by using specially fabricated *** design of the liquid camera ensures that the multi-layers of the real 3D scene can be obtained quickly and with great imaging *** EEPMD-Net takes the information of real 3D scene as the input,and uses two new structures of encoder and decoder networks to realize low-noise phase *** comparing the intensity information between the reconstructed image after depth fusion and the target scene,the composite loss function is constructed for phase optimization,and the high-fidelity training of hologram with true depth of the 3D scene is realized for the first *** holographic camera achieves the high-fidelity and fast generation of the hologram of the real 3D scene,and the reconstructed experiment proves that the holographic image has the advantage of low *** proposed holographic camera is unique and can be used in 3D display,measurement,encryption and other fields.

关键词： calculation solution holographic

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An End-to-End Two-Branch Network Towards Robust Video Fingerprinting

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第5期5卷 2371-2384页

作者： Xu, Yingying Zhou, Yuanding Li, Xinran Zhao, Gejian Qin, Chuan University of Shanghai for Science and Technology School of Optical-Electrical and Computer Engineering Shanghai200093 China

With the increasing number of edited videos, many robust video fingerprinting schemes have been proposed to solve the problem of video content authentication. However, most of them either deal with the temporal and spatial features symmetrically or insufficiently consider the temporal information. In this work, an end-to-end two-branch network toward robust video fingerprinting (RVFNet) is proposed, where the two branches focus on the temporal and spatial information, respectively. The temporal branch aims to comprehensively capture complex motion patterns by combining subtle motion changes with the overall motion trend. The spatial branch exploits the pixel-level information obtained by multiple receptive fields while preserving significant structural features. Deep metric learning is employed in the training process, and we adopt hard triplet loss to constrain the generation of fingerprints. Furthermore, we construct a large-scale and complex dataset for the robust video fingerprinting task based on multiple video content-preserving manipulations in actual scenarios. The size of our dataset exceeds most datasets adopted in the current robust video fingerprinting schemes. Based on the proposed dataset, experimental results demonstrate that our scheme achieves outstanding performance improvements compared with the state of the art. © 2020 IEEE.

关键词： Convolution

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Unsupervised anomaly detection and localization via bidirectional knowledge distillation

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Neural Computing and Applications 2024年第29期36卷 18499-18514页

作者： Wang, Xiaoming Wang, Yongxiong Pan, Zhiqun Wang, Guangpeng School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China

Knowledge distillation has demonstrated significant potential in addressing the challenge of unsupervised anomaly detection (AD). The representation discrepancy of anomalies in the teacher–student (T-S) model provides evidence for anomaly detection and localization. However, the teacher model is pretrained for classification, while the anomaly scores in the distillation-based anomaly detection method are indirectly derived from the classification scores. The mismatch between the two tasks can hinder the optimization of the model. To tackle this issue, we propose an innovative bidirectional knowledge distillation model. In this approach, forward knowledge distillation is pivotal in bolstering the model’s capacity for generalization. Simultaneously, backward knowledge distillation promotes diversity in representing anomalies. This reciprocal knowledge exchange effectively wards off potential performance declines due to target inconsistency. Through bidirectional knowledge distillation, we establish a more encompassing and resilient framework for knowledge transfer. Additionally, we introduce a novel data augmentation strategy to simulate anomalies and effectively eliminate unnecessary noise. In experiments on the MVTec AD, the proposed model achieves competitive results compared to state-of-the-art methods, 97.47% on image-level AUC, 98.23% on pixel-level AUC, and 94.77% on instance-level PRO. These results demonstrate the practicality of our approach in anomaly detection and localization. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Anomaly detection

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Super-resolution reconstruction of off-axis digital holography based on Real-ESRGAN

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Applied Optics 2025年第9期64卷 2245-2254页

作者： Chen, Geng Chen, Jie Liao, Houzhang Liu, Keke Tang, Xin Kong, Yong School of Electric and Electrical Engineering Shanghai University of Engineering Science Shanghai201620 China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China

Off-axis digital holography plays a crucial role in high-precision three-dimensional imaging. However, high-resolution phase images are often affected by the limited pixel size of the sensor. To address this issue, this study proposes, for the first time, to the best of our knowledge, the application of Real-ESRGAN for the super-resolution reconstruction of off-axis digital holography images. By directly applying super-resolution processing to the hologram, the limitations of the sensor's pixel size are overcome, followed by phase reconstruction to obtain high-resolution phase images. The Real-ESRGAN model enhances the texture information of the hologram through a deep network with multiple residual-in-residual dense blocks (RRDBs), restoring a clearer hologram. A U-Net architecture with spectral normalization, offering stronger discriminative capability, is used to provide detailed per-pixel feedback for the generator. The experimental results demonstrate that this method can be applied to multi-scale holograms, outperforming comparison networks in both visual quality and quantitative metrics, thus providing an innovative solution for the super-resolution reconstruction of off-axis digital holography. © 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Holograms

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More than just a name?From magnetic to optical skyrmions and the topology of light

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Light(Science & Applications) 2025年第1期14卷 26-29页

作者： Jian Chen Andrew Forbes Cheng-Wei Qiu School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai200093China Department of Electrical and Computer Engineering National University of SingaporeSingapore117583Singapore School of Physics University of the WitwatersrandJohannesburgSouth Africa

Topology is usually perceived intrinsically immutable for a given *** argue that optical topologies do not immediately enjoy such ***'optical skyrmions'as an example,we show that they will exhibit varying textures and topological invariants(skyrmion numbers),depending on how to construct the skyrmion vector when projecting from real to parameter *** demonstrate the fragility of optical skyrmions under a ubiquitous scenario-simple reflection off an optical *** topology is not without benefit,but it must not be assumed.

关键词： numbers space. topology

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Alkali Atomic Density Detection with Arbitrarily Polarized Light

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IEEE Sensors Journal 2025年第11期25卷 20466-20473页

作者： Liu, Xuejing Wang, Menglu Li, Yuhan Wang, Yangtao Zhang, Xuedian Li, Yang University of Shanghai for Science and Technology Key Laboratory of Optical Technology and Instrument for Medicine Ministry of Education School of Optical-Electrical and Computer Engineering Shanghai200093 China University of Shanghai for Science and Technology School of Optical-Electrical and Computer Engineering Shanghai200093 China Tongji University Shanghai Institute of Intelligent Science and Technology Shanghai200093 China

The atomic density of an alkali vapor cell is a critical factor in determining the performance of atomic magnetometers. This paper presents a novel method to detect the density of an alkali atomic ensemble under arbitrary polarization states. By establishing a comprehensive model that correlates the absorption spectrum with the incident light’s polarization, our approach enables real-time and flexible measurements across varying temperatures and polarization angles. Experimental validations are conducted by systematically rotating a quarter-wave plate and controlling the vapor cell temperature, thereby collecting transmission spectra at multiple polarizations. The results demonstrate that the proposed method simplifies density measurements while preserving high accuracy, laying a solid foundation for further research on Spin-Exchange Relaxation-Free (SERF) atomic magnetometers. This technique serves as a versatile and effective tool for in-situ monitoring of alkali metal vapor density in various sensor applications. © 2001-2012 IEEE.

关键词： Absorption spectroscopy

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