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Acousto-optic modulator-based bi-frequency interferometer for quantum technology

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Chinese Optics Letters 2024年第2期22卷 186-191页

作者：李文奇邓琦琦郭学石李小英 College of Precision Instrument and Opto-electronics Engineering Key Laboratory of Opto-Electronics Information TechnologyMinistry of EducationTianjin UniversityTianjin 300072China

We demonstrate a high-performance acousto-optic modulator-based bi-frequency interferometer,which can realize either beating or beating free interference for a single-photon level quantum *** and optical efficiency of the interferometer are(99.5±0.2)%and(95±1)%,*** phase of the interferometer is actively stabilized by using a dithering phase-locking scheme,where the phase dithering is realized by directly driving the acousto-optic modulators with a specially designed electronic *** further demonstrate applications of the interferometer in quantum technology,including bi-frequency coherent combination,frequency tuning,and optical *** results show the interferometer is a versatile device for multiple quantum technologies.

关键词： bi-frequency interferometer acousto-optic modulator quantum optics quantum manipulation

Joint Rain Streaks & Haze Removal Network for Object Detection

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Computers, Materials & Continua 2024年第6期79卷 4683-4702页

作者： Ragini Thatikonda Prakash Kodali Ramalingaswamy Cheruku Eswaramoorthy K.V department of electronics and Communication Engineering National Institute of TechnologyWarangal506004India department of Computer Science and Engineering National Institute of TechnologyWarangal506004India department of electronics and Communication Engineering Indian Institute of Information TechnologyDesign and ManufacturingKurnool518008India

In the realm of low-level vision tasks,such as image deraining and dehazing,restoring images distorted by adverse weather conditions remains a significant *** emergence of abundant computational resources has driven the dominance of deep Convolutional Neural Networks(CNNs),supplanting traditional methods reliant on prior ***,the evolution of CNN architectures has tended towards increasing complexity,utilizing intricate structures to enhance performance,often at the expense of computational *** response,we propose the Selective Kernel Dense Residual M-shaped Network(SKDRMNet),a flexible solution adept at balancing computational efficiency with network accuracy.A key innovation is the incorporation of an M-shaped hierarchical structure,derived from the U-Net framework as M-Network(M-Net),within which the Selective Kernel Dense Residual Module(SDRM)is introduced to reinforce multi-scale semantic feature *** methodology employs two sampling techniques-bilinear and pixel unshuffled and utilizes a multi-scale feature fusion approach to distil more robust spatial feature map *** the reconstruction phase,feature maps of varying resolutions are seamlessly integrated,and the extracted features are effectively merged using the Selective Kernel Fusion Module(SKFM).Empirical results demonstrate the comprehensive superiority of SKDRMNet across both synthetic and real rain and haze datasets.

关键词： Image deraining Selective Dense Residual Module(SDRM) Selective Kernel Fusion Module(SKFM) Selective KernelDense Residual M-Shaped Network(SKDRMNet)

A Fully-Integrated Memristor Chip for Edge Learning

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Nano-Micro Letters 2024年第9期16卷 123-127页

作者： Yanhong Zhang Liang Chu Wenjun Li School of electronics and information Hangzhou Dianzi UniversityHangzhou 310018People’s Republic of China

It is still challenging to fully integrate computing in memory chip as edge learning *** recent work published on Science,a fully-integrated chip based on neuromorphic memristors was developed for edge learning as artificial neural networks with functionality of synapses,dendrites,and somas.A crossbar-array memristor chip facilitated edge learning including hardware realization,learning algorithm,and cycle-parallel sign-and threshold-based learning(STELLAR)*** motion control and demonstration platforms were executed to improve the edge learning ability for adapting to new scenarios.

关键词： Computing in memory Edge learning Fully-integrated chip

A Deformable Network with Attention Mechanism for Retinal Vessel Segmentation

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Journal of Beijing Institute of Technology 2024年第3期33卷 186-193页

作者： Xiaolong Zhu Wenjian Li Weihang Zhang Dongwei Li Huiqi Li School of information and electronics Beijing Institute of TechnologyBeijing 100081China

The intensive application of deep learning in medical image processing has facilitated the advancement of automatic retinal vessel segmentation *** overcome the limitation that traditional U-shaped vessel segmentation networks fail to extract features in fundus image sufficiently,we propose a novel network(DSeU-net)based on deformable convolution and squeeze excitation residual *** deformable convolution is utilized to dynamically adjust the receptive field for the feature extraction of retinal *** the squeeze excitation residual module is used to scale the weights of the low-level features so that the network learns the complex relationships of the different feature layers *** validate the DSeU-net on three public retinal vessel segmentation datasets including DRIVE,CHASEDB1,and STARE,and the experimental results demonstrate the satisfactory segmentation performance of the network.

关键词： retinal vessel segmentation deformable convolution attention mechanism deep learning

A Cover-Independent Deep Image Hiding Method Based on Domain Attention Mechanism

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Computers, Materials & Continua 2024年第3期78卷 3001-3019页

作者： Nannan Wu Xianyi Chen James Msughter Adeke Junjie Zhao School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China School of electronics and information Engineering Nanjing University of Information Science and TechnologyNanjing210044China

Recently,deep image-hiding techniques have attracted considerable attention in covert communication and high-capacity information ***,these approaches have some *** example,a cover image lacks self-adaptability,information leakage,or weak *** address these issues,this study proposes a universal and adaptable image-hiding ***,a domain attention mechanism is designed by combining the Atrous convolution,which makes better use of the relationship between the secret image domain and the cover image ***,to improve perceived human similarity,perceptual loss is incorporated into the training *** experimental results are promising,with the proposed method achieving an average pixel discrepancy(APD)of 1.83 and a peak signal-to-noise ratio(PSNR)value of 40.72 dB between the cover and stego images,indicative of its high-quality ***,the structural similarity index measure(SSIM)reaches 0.985 while the learned perceptual image patch similarity(LPIPS)remarkably registers at ***,self-testing and cross-experiments demonstrate the model’s adaptability and generalization in unknown hidden spaces,making it suitable for diverse computer vision tasks.

关键词： Deep image hiding attention mechanism privacy protection data security visual quality

A Method of Generating Semi-Experimental Biomedical Datasets

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Journal of Beijing Institute of Technology 2024年第3期33卷 219-226页

作者： Jing Wang Naike Du Zi He Xiuzhu Ye School of information and electronics Beijing Institute of TechnologyBeijing 100081China

This paper proposed a method to generate semi-experimental biomedical datasets based on full-wave simulation *** system noise such as antenna port couplings is fully considered in the proposed datasets,which is more realistic than synthetical *** this paper,datasets containing different shapes are constructed based on the relative permittivities of human ***,a back-propagation scheme is used to obtain the rough reconstructions,which will be fed into a U-net convolutional neural network(CNN)to recover the high-resolution *** results show that the network trained on the datasets generated by the proposed method can obtain satisfying reconstruction results and is promising to be applied in real-time biomedical imaging.

关键词： electromagnetic imaging dataset biomedical imaging

Research on dynamic measurement method of speckle in laser display

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Optoelectronics Letters 2024年第6期20卷 360-366页

作者： LIU Hong LIU Yaning ZHANG Xiaoyu School of electronics information Shanghai Dianji UniversityShanghai 201306China

Laser display technology is the most promising display technology in the market and is widely used in many fields. However, laser speckle has been troubling the application and expansion of this technology in some fields. In order to better evaluate the speckle, speckle measurement methods must be studied. In this study, a dynamic measurement method for laser speckles is proposed according to the optical superposition characteristics of speckle, which can reduce the influence of non-coherent factors on the speckle measurement results. The feasibility of the dynamic speckle measurement method is verified by designing an experimental scheme.

关键词： Research on dynamic measurement method of speckle in laser display

A Deep Learning Method to Process Scattered Field Data in Biomedical Imaging System

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Journal of Beijing Institute of Technology 2024年第3期33卷 213-218页

作者： Jing Wang Naike Du Xiuzhu Ye School of information and electronics Beijing Institute of TechnologyBeijing 100081China

This paper proposed a deep-learning-based method to process the scattered field data of transmitting antenna,which is unmeasurable in inverse scattering system because the transmitting and receiving antennas are multiplexed.A U-net convolutional neural network(CNN)is used to recover the scattered field data of each transmitting *** numerical results proved that the proposed method can complete the scattered field data at the transmitting antenna which is unable to measure in the actual experiment and can also eliminate the reconstructed error caused by the loss of scattered field data.

关键词： inverse problem scattered field deep learning

Improving the Effectiveness of Image Classification Structural Methods by Compressing the Description According to the information Content Criterion

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Computers, Materials & Continua 2024年第8期80卷 3085-3106页

作者： Yousef Ibrahim Daradkeh Volodymyr Gorokhovatskyi Iryna Tvoroshenko Medien Zeghid department of Computer Engineering and information College of Engineering inWadi AlddawasirPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia department of Informatics Kharkiv National University of Radio ElectronicsKharkiv61166Ukraine electronics and Micro-electronics Laboratory Faculty of SciencesUniversity of MonastirMonastir5000Tunisia

The research aims to improve the performance of image recognition methods based on a description in the form of a set of keypoint *** main focus is on increasing the speed of establishing the relevance of object and etalon descriptions while maintaining the required level of classification *** class to be recognized is represented by an infinite set of images obtained from the etalon by applying arbitrary geometric *** is proposed to reduce the descriptions for the etalon database by selecting the most significant descriptor components according to the information content *** informativeness of an etalon descriptor is estimated by the difference of the closest distances to its own and other *** developed method determines the relevance of the full description of the recognized object with the reduced description of the *** practical models of the classifier with different options for establishing the correspondence between object descriptors and etalons are *** results of the experimental modeling of the proposed methods for a database including images of museum jewelry are *** test sample is formed as a set of images from the etalon database and out of the database with the application of geometric transformations of scale and rotation in the field of *** practical problems of determining the threshold for the number of votes,based on which a classification decision is made,have been *** has revealed the practical possibility of tenfold reducing descriptions with full preservation of classification *** the descriptions by twenty times in the experiment leads to slightly decreased *** speed of the analysis increases in proportion to the degree of *** use of reduction by the informativeness criterion confirmed the possibility of obtaining the most significant subset of features for classification,which guarantees a decent

关键词： Description reduction description relevance descriptor image classification information content keypoint processing speed