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Towards an intelligent photonic system

science China(Information sciences) 2020年第6期63卷 80-96页

作者： Weiwen ZOU Bowen MA Shaofu XU Xiuting ZOU Xingjun WANG State Key Laboratory of Advanced Optical Communication Systems and Networks Intelligent Microwave Lightwave Integration Innovation Center (iMLic) Department of Electronic EngineeringShanghai Jiao Tong University State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University

The emerging intelligence technologies represented by deep learning have broadened their applications to various fields. Beyond the conventional electronics-based processing systems, the convergence of photonics and artificial intelligence(AI) technology enhances the performance and learning ability of AI. In this review, we propose the concept of an intelligent photonic system(IPS), illustrating it as a developing architecture with three different versions. For each version of IPS, we review several representative *** we discuss the challenges towards an IPS and provide some prospects for the future development.

关键词： intelligent photonic system deep learning artificial intelligence optical neural network neuromorphic photonics

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A design method for high fabrication tolerance integrated optical mode multiplexer

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science China(Information sciences) 2020年第6期63卷 184-194页

作者： Bitao SHEN Haowen SHU Linjie ZHOU Xingjun WANG State Key Laboratory on Advanced Optical Communication Systems and Networks Department of ElectronicsSchool of Electronics Engineering and Computer Science Peking University State Key Laboratory of Advanced Optical Communication Systems and Networks Department of Electronic Engineering Shanghai Jiao Tong University Nano-optoelectronics Frontier Center of Ministry of Education Peking University

The tapered asymmetric directional coupler has the potential to realize high fabrication tolerance and high transmission efficiency on-chip mode multiplexer. However, the geometry parameter selection of tapered structure remains empirical. In this paper, we propose a design method for the tapered structure based on genetic algorithm. Combined with the adjusted coupling equations and interpolation method, lowtime-cost optimization can be realized. Three mode multiplexers(TE0&TE1, TE0&TE2 and TE0&TE5)are designed by our method. According to simulation results, the insertion loss of the designed devices is lower than 1.8 dB and the crosstalk is lower than-15 dB when the fabrication error is within required range(±10 nm for TE0&TE2 and TE0&TE5, and ±20 nm for TE0&TE1) in the bandwidth of 1.5–1.6 μm. In addition, the entire optimization process takes only 2 h for each device, which is around the time cost of a single 3 D simulation.

关键词： mode multiplexer directional coupler taper structure coupled-mode theory genetic algorithm

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ST-KeyS: Self-Supervised Transformer for Keyword Spotting in Historical Handwritten Documents

arXiv

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arXiv 2023年

作者： Jemni, Sana Khamekhem Ammar, Sourour Souibgui, Mohamed Ali Kessentini, Yousri Cheddad, Abbas Digital Research Center of Sfax B.P. 275 Sakiet Ezzit Sfax3021 Tunisia Laboratory of Signals systems Artificial Intelligence and networks Sfax Tunisia Multimedia Information systems and Advanced Computing Laboratory Tunisia Computer Vision Center Computer Science Department Universitat Autònoma de Barcelona Spain Department of Computer Science Blekinge Institute of Technology Karlskrona Sweden

Keyword spotting (KWS) in historical documents is an important tool for the initial exploration of digitized collections. Nowadays, the most efficient KWS methods are relying on machine learning techniques that require a large amount of annotated training data. However, in the case of historical manuscripts, there is a lack of annotated corpus for training. To handle the data scarcity issue, we investigate the merits of the self-supervised learning to extract useful representations of the input data without relying on human annotations and then using these representations in the downstream task. We propose ST-KeyS, a masked auto-encoder model based on vision transformers where the pretraining stage is based on the mask-and-predict paradigm, without the need of labeled data. In the fine-tuning stage, the pre-trained encoder is integrated into a siamese neural network model that is fine-tuned to improve feature embedding from the input images. We further improve the image representation using pyramidal histogram of characters (PHOC) embedding to create and exploit an intermediate representation of images based on text attributes. In an exhaustive experimental evaluation on three widely used benchmark datasets (Botany, Alvermann Konzilsprotokolle and George Washington), the proposed approach outperforms state-of-the-art methods trained on the same datasets. © 2023, CC BY.

关键词： Image enhancement

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Applying Explanatory Artificial Intelligence Using LIME to Analyze Arabic Online Handwriting Recognition Models

Applying Explanatory Artificial Intelligence Using LIME to A...

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International Conference on Information Networking

作者： Hasanien Ali Talib Alothman Wafa Lejmi Safa Ameur Mohamed Ali Mahjoub ISITCom - Higher Institute of Computer Science and Communication Sousse Tunisia LATIS - Laboratory of Advanced Technology and Intelligent Systems National Engineering School of Sousse (ENISo) University of Sousse Sousse Tunisia Mechatronics Engineering Department University of Mosul Mosul Iraq

ISBN: (数字)9798331506940

ISBN: (纸本)9798331506957

This study applies interpretable artificial intelligence (XAI) techniques in an unprecedented way to improve transparency in online Arabic handwriting recognition models. By using the LIME (Local Model-Independent Explanations) technique to analyze and interpret a convolutional neural network (CNN) model trained on the ADAB dataset. LIME highlights the key features that the model relies on in handwriting recognition. This research demonstrates the effectiveness of the LIME technique in uncovering the factors that the model relies on in an unconventional way and provides detailed explanations of how the decisions are made, which enhances transparency and increases users’ confidence in these models. The results provide useful information for improving the performance of handwriting recognition systems and a beginning for applying XAI techniques on a larger scale, including using more complex datasets and additional interpretation techniques to gain a deeper understanding of how models work with different handwriting styles. This study paves the way for the use of interpretable techniques in the field of Arabic handwriting recognition.

关键词： Deep learning Handwriting recognition Analytical models Explainable AI Shape Decision making Predictive models Prediction algorithms Data models Convolutional neural networks

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Holographic-Pattern Based Multi-User Beam Training in RHS-Aided Hybrid Near-Field and Far-Field Communications

arXiv

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arXiv 2024年

作者： Zhang, Shupei Di, Boya Kaushik, Aryan Eldar, Yonina C. State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing China The Department of Computing & Mathematics Manchester Metropolitan University United Kingdom The Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot7610001 Israel

Reconfigurable holographic surfaces (RHSs) have been suggested as an energy-efficient solution for extremely large-scale arrays. By controlling the amplitude of RHS elements, high-gain directional holographic patterns can be achieved. However, the complexity of acquiring real-time channel state information (CSI) for beamforming is exceedingly high, particularly in large-scale RHS-assisted communications, where users may distribute in the near-field region of RHS. This paper proposes a one-shot multi-user beam training scheme in large-scale RHS-assisted systems applicable to both near and far fields. The proposed beam training scheme comprises two phases: angle search and distance search, both conducted simultaneously for all users. For the angle search, an RHS angular codebook is designed based on holographic principles so that each codeword covers multiple angles in both near-field and far-field regions, enabling simultaneous angular search for all users. For the distance search, we construct the distance-adaptive codewords covering all candidate angles of users in a real-time way by leveraging the additivity of holographic patterns, which is different from the traditional phase array case. Simulation results demonstrate that the proposed scheme achieves higher system throughput compared to traditional beam training schemes. The beam training accuracy approaches the upper bound of exhaustive search at a significantly reduced overhead. Copyright © 2024, The Authors. All rights reserved.

关键词： Beamforming

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Retraction Note: Differences between CeO2-doped sodium borate glass and Cu2O3-doped sodium borate glass in terms of structural defects concentration and plasmon frequency

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Optical and Quantum Electronics 2025年第4期57卷 1-2页

作者： Gomaa, Hosam M. Saudi, H. A. Zahran, H. Y. Yahia, I. S. Pharaohs-Higher Institute for Computer Information Systems and Management Giza Egypt Department of Physics Faculty of Science Al-Azhar University (Girls’ Branch) Nasr City Egypt Laboratory of Nano-Smart Materials for Science and Technology (LNSMST) Department of Physics Faculty of Science King Khalid University Abha Saudi Arabia Research Center for Advanced Materials Science (RCAMS) King Khalid University Abha Saudi Arabia

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St-Keys: Self-Supervised Transformer for Keyword Spotting in Historical Handwritten Documents

SSRN

引用

SSRN 2023年

作者： Jemni, Sana Khamekhem Ammar, Sourour Souibgui, Mohamed Ali Kessentini, Yousri Cheddad, Abbas Digital Research Center of Sfax B.P. 275 Sakiet Ezzit Sfax3021 Tunisia SM@RTS: Laboratory of Signals systeMs aRtificial Intelligence and neTworkS MIR@CL: Multimedia InfoRmation systems and Advanced Computing Laboratory Computer Vision Center Computer Science Department Universitat Aut`onoma de Barcelona Spain Department of Computer Science Blekinge Institute of Technology Karlskrona Sweden

Keyword spotting (KWS) in historical documents is an important tool for the initial exploration of digitized collections. Nowadays, the most efficient KWS methods are relying on machine learning techniques that require a large amount of annotated training data. However, in the case of historical manuscripts, there is a lack of annotated corpus for training. To handle the data scarcity issue, we investigate the merits of the self-supervised learning to extract useful representations of the input data without relying on human annotations and then using these representations in the downstream task. We propose ST-KeyS, a masked auto-encoder model based on vision transformers where the pretraining stage is based on the mask-and-predict paradigm, without the need of labeled data. In the fine-tuning stage, the pre-trained encoder is integrated into a siamese neural network model that is fine-tuned to improve feature embedding from the input images. We further improve the image representation using pyramidal histogram of characters (PHOC) embedding to create and exploit an intermediate representation of images based on text attributes. In an exhaustive experimental evaluationon three widely used benchmark datasets (Botany, Alvermann Konzilsprotokolle and George Washington), the proposed approach outperforms state-of-the-art methods trained on the same datasets. © 2023, The Authors. All rights reserved.

关键词： Embeddings

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Co‑packaged optics(CPO):status,challenges,and solutions

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Frontiers of Optoelectronics 2023年第1期16卷 1-40页

作者： Min Tan Jiang Xu Siyang Liu Junbo Feng Hua Zhang Chaonan Yao Shixi Chen Hangyu Guo Gengshi Han Zhanhao Wen Bao Chen Yu He Xuqiang Zheng Da Ming Yaowen Tu Qiang Fu Nan Qi Dan Li Li Geng Song Wen Fenghe Yang Huimin He Fengman Liu Haiyun Xue Yuhang Wang Ciyuan Qiu Guangcan Mi Yanbo Li Tianhai Chang Mingche Lai Luo Zhang Qinfen Hao Mengyuan Qin 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 Electronic and Computer Engineering The Hong Kong University of Science and TechnologyHong KongChina HKUST Fok Ying Tung Research Institute Guangzhou 511462China The Hong Kong University of Science and Technology(Guangzhou) Guangzhou 511462China Chongqing United Micro-Electronics Center(CUMEC) Chongqing 401332China Hisense Broadband Multimedia Technologies Co. Ltd.Qingdao 266000China Institute of Microelectronics Chinese Academy of SciencesBeijing 100029China State Key Laboratory of Superlattices and Microstructures Institute of SemiconductorsChinese Academy of SciencesBeijing 100083China School of Microelectronics Xi’an Jiaotong UniversityXi’an 710049China Zhangjiang Laboratory Shanghai 201210China The State Key Laboratory of Advanced Optical Communication Systems and Networks Department of Electronic EngineeringShanghai Jiao Tong UniversityShanghai 200240China Huawei Technologies Co. Ltd.Shenzhen 440307China College of Computer National University of Defense TechnologyChangsha 410073China Institute of Computing Technology Chinese Academy of SciencesBeijing 100086China

Due to the rise of 5G,IoT,AI,and high-performance computing applications,datacenter trafc has grown at a compound annual growth rate of nearly 30%.Furthermore,nearly three-fourths of the datacenter trafc resides within *** conventional pluggable optics increases at a much slower rate than that of datacenter *** gap between application requirements and the capability of conventional pluggable optics keeps increasing,a trend that is *** optics(CPO)is a disruptive approach to increasing the interconnecting bandwidth density and energy efciency by dramatically shortening the electrical link length through advanced packaging and co-optimization of electronics and *** is widely regarded as a promising solution for future datacenter interconnections,and silicon platform is the most promising platform for large-scale *** international companies(e.g.,Intel,Broadcom and IBM)have heavily investigated in CPO technology,an inter-disciplinary research feld that involves photonic devices,integrated circuits design,packaging,photonic device modeling,electronic-photonic co-simulation,applications,and *** review aims to provide the readers a comprehensive overview of the state-of-the-art progress of CPO in silicon platform,identify the key challenges,and point out the potential solutions,hoping to encourage collaboration between diferent research felds to accelerate the development of CPO technology.

关键词： Co-packaged optics Silicon photonics High-performance computing advanced packaging External laser Optical power delivery Co-simulation Standardization Transmitter Receiver

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Submilliwatt, widely tunable coherent microcomb generation with feedback-free operation

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advanced Photonics 2023年第3期5卷 144-154页

作者： Haowen Shu Lin Chang Chenghao Lao Bitao Shen Weiqiang Xie Xuguang Zhang Ming Jin Yuansheng Tao Ruixuan Chen Zihan Tao Huajin Chang Shaohua Yu Qifan Yang Xingjun Wang John E.Bowers Peking University School of ElectronicsState Key Laboratory of Advanced Optical Communication Systems and NetworksBeijingChina University of California Santa BarbaraDepartment of Electrical and Computer EngineeringSanta BarbaraCaliforniaUnited States Peking University School of PhysicsState Key Laboratory for Artificial Microstructure and Mesoscopic PhysicsBeijingChina Peng Cheng Laboratory ShenzhenChina Peking University Frontiers Science Center for Nano-OptoelectronicsBeijingChina

Microcombs are revolutionizing optoelectronics by providing parallel, mutually coherent wavelengthchannels for time-frequency metrology and information processing. To implement this essential function inintegrated photonic systems, it is desirable to drive microcombs directly with an on-chip laser in a simpleand flexible way. However, two major difficulties have prevented this goal: (1) generating mode-lockedcomb states usually requires a significant amount of pump power and (2) the requirement to align laser andresonator frequency significantly complicates operation and limits the tunability of the comb lines. Here, weaddress these problems by using microresonators on an AlGaAs on-insulator platform to generate dark-pulsemicrocombs. This highly nonlinear platform dramatically relaxes fabrication requirements and leads to arecord-low pump power of <1 mW for coherent comb generation. Dark-pulse microcombs facilitated bythermally controlled avoided mode crossings are accessed by direct distributed feedback laser *** any feedback or control circuitries, the comb shows good coherence and stability. With around150 mW on-chip power, this approach also leads to an unprecedentedly wide tuning range of over one freespectral range (97.5 GHz). Our work provides a route to realize power-efficient, simple, and reconfigurablemicrocombs that can be seamlessly integrated with a wide range of photonic systems.

关键词： dark-pulse microcomb direct pumping scheme widely tunable source

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Diagnosis of Diabetes Type Using Random Forest Algorithm and SVM for Improving Accuracy 1

引用

International Conference on Advances in Communication Technology and computer Engineering, ICACTCE 2023

作者： Hai, Tao Zhou, Jincheng Olatunji, Timothy A. Ajoboh, Oluwakemi A. Chen, Lee Iwendi, Celestine Omeoga, Nkechi Sinha, Anurag School of Computer and Information Qiannan Normal University for Nationalities Guizhou Duyun558000 China Key Laboratory of Advanced Manufacturing Technology of the Ministry of Education Guizhou University Guizhou Guiyang550025 China School of Information and Artificial Intelligence Nanchang Institute of Science and Technology Nanchang China Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Province Duyun558000 China Key Laboratory of Complex Systems and Intelligent Optimization of Qiannan Duyun558000 China School of Creative Technologies University of Bolton BoltonBL3 5AB United Kingdom Manchester Metropolitan University Manchester United Kingdom Department of Computer Science and Information Technology IGNOU New Delhi India

ISBN: (数字)9783031371646

ISBN: (纸本)9783031371639

To improve the accuracy in the detection of diabetes-type diagnosis using Random Forest Algorithm and Support Vector Method. A dataset on diabetes was collected on ***. Support vector method analysis was performed on the data using kernel as linear, poly, and rbf with random state = 42 and test size = 0.2. The Random Forest Algorithm with n_estimators = 100 has the same accuracy as the support vector method with the kernel as rbf. When it comes to type diagnosis for a patient having diabetes, the Random Forest Algorithm and Support Vector Method with kernel rbf can be used, unlike another kernel of the Support Vector Method. The dataset was also visualized using power. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Radial basis function networks

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