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3DTeethSeg’22: 3D Teeth Scan Segmentation and Labeling Challenge

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arXiv 2023年

作者： Ben-Hamadou, Achraf Smaoui, Oussama Rekik, Ahmed Pujades, Sergi Boyer, Edmond Lim, Hoyeon Kim, Minchang Lee, Minkyung Chung, Minyoung Shin, Yeong-Gil Leclercq, Mathieu Cevidanes, Lucia Prieto, Juan Carlos Zhuang, Shaojie Wei, Guangshun Cui, Zhiming Zhou, Yuanfeng Dascalu, Tudor Ibragimov, Bulat Yong, Tae-Hoon Ahn, Hong-Gi Kim, Wan Han, Jae-Hwan Choi, Byungsun van Nistelrooij, Niels Kempers, Steven Vinayahalingam, Shankeeth Strippoli, Julien Thollot, Aurélien Setbon, Hugo Trosset, Cyril Ladroit, Edouard Centre de Recherche en Numérique de Sfax Laboratory of Signals Systems Artificial Intelligence and Networks Technopôle de Sfax Sfax3021 Tunisia Udini 37 BD Aristide Briand Aix-en-Provence13100 France Inria Univ. Grenoble Alpes CNRS Grenoble INP LJK France Department of Computer Science and Engineering Seoul National University Korea Republic of School of Software Soongsil University Korea Republic of University of Michigan Ann Arbor United States University of North Carolina Chapel Hill United States Shandong University China ShanghaiTech University China Department of Computer Science University of Copenhagen Denmark Osstem Implant Co. Ltd. Seoul Korea Republic of Department of Oral and Maxillofacial Surgery Radboud University Nijmegen Medical Centre P.O. Box 9101 Nijmegen6500 HB Netherlands Department of Computing Science Radboud University Nijmegen Netherlands Department of Artificial Intelligence Radboud University Nijmegen Netherlands Berlin Institute of Health at Charité Universitätsmedizin Berlin Charitéplatz 1 Berlin10117 Germany

Teeth localization, segmentation, and labeling from intra-oral 3D scans are essential tasks in modern dentistry to enhance dental diagnostics, treatment planning, and population-based studies on oral health. However, developing automated algorithms for teeth analysis presents significant challenges due to variations in dental anatomy, imaging protocols, and limited availability of publicly accessible data. To address these challenges, the 3DTeethSeg’22 challenge was organized in conjunction with the International Conference on Medical Image Computing and computer Assisted Intervention (MICCAI) in 2022, with a call for algorithms tackling teeth localization, segmentation, and labeling from intraoral 3D scans. A dataset comprising a total of 1800 scans from 900 patients was prepared, and each tooth was individually annotated by a human-machine hybrid algorithm. A total of 6 algorithms were evaluated on this dataset. In this study, we present the evaluation results of the 3DTeethSeg’22 challenge. The 3DTeethSeg’22 challenge code can be accessed at: https://***/abenhamadou/3DTeethSeg22 challenge. © 2023, CC BY-SA.

关键词： Object detection

Multiple residual dense networks for reconfigurable intelligent surfaces cascaded channel estimation

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arXiv 2021年

作者： Jin, Yu Zhang, Jiayi Huang, Chongwen Yang, Liang Xiao, Huahua Ai, Bo Wang, Zhiqin The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University Beijing100044 China Zhejiang Provincial Key Lab of Information Processing Communication and Networking Zhejiang University Hangzhou310007 China College of Computer Science and Electronic Engineering Hunan University Changsha410082 China ZTE Corporation State Key Laboratory of Mobile Network Mobile Multimedia Technology Shenzhen518057 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen518055 China China Academy of Information and Communications Technology Beijing100191 China

Reconfigurable intelligent surface (RIS) constitutes an essential and promising paradigm that relies programmable wireless environment and provides capability for space-intensive communications, due to the use of low-cost massive reflecting elements over the entire surfaces of man-made structures. However, accurate channel estimation is a fundamental technical prerequisite to achieve the huge performance gains from RIS. By leveraging the low rank structure of RIS channels, three practical residual neural networks, named convolutional blind denoising network, convolutional denoising generative adversarial networks and multiple residual dense network, are proposed to obtain accurate channel state information, which can reflect the impact of different methods on the estimation performance. Simulation results reveal the evolution direction of these three methods and reveal their superior performance compared with existing benchmark schemes. Copyright © 2021, The Authors. All rights reserved.

关键词： Channel estimation

New characterizations for the multi-output correlation-immune boolean functions

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arXiv 2019年

作者： Chai, Jinjin Wang, Zilong Mesnager, Sihem Gong, Guang State Key Laboratory of Integrated Service Networks School of Cyber Engineering Xidian University Department of Mathematics University of Paris XIII Department of Electrical and Computer Engineering University of Waterloo

Correlation-immune (CI) multi-output Boolean functions have the property of keeping the same output distribution when some input variables are fixed. Recently, a new application of CI functions has appeared in the system of resisting side-channel attacks (SCA). In this paper, three new methods are proposed to characterize the t th-order CI multi-output Boolean functions (n-input and m-output). The first characterization is to regard the multi-output Boolean functions as the corresponding generalized Boolean functions. It is shown that a generalized Boolean functions fg is a t th-order CI function if and only if the Walsh transform of fg defined here vanishes at all points with Hamming weights between 1 and t. Compared to the previous Walsh transforms of component functions, our first method can reduce the computational complexity from (2m − 1) Ptj=1 (nj ) to m Ptj=1 (nj ). The last two methods are generalized from Fourier spectral characterizations. Especially, Fourier spectral characterizations are more efficient to characterize the symmetric multi-output CI Boolean functions.42A38, 94A60, 06E30 Copyright © 2019, The Authors. All rights reserved.

关键词： Discrete Fourier transforms

Multitemporal Hyperspectral Image Classification using Collaborative Representation-based Classification with Tikhonov Regularization

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Multitemporal Hyperspectral Image Classification using Colla...

International Workshop on the Analysis of Multi-temporal Remote Sensing Images (MultiTemp)

作者： Chiru Ge Qian Du Yunsong Li Jiaojiao Li The State Key Laboratory of Integrated Services Networks Xidian University Xi'an China The Department of Electrical and Computer Engineering Mississippi State University Starkville USA

A covariance alignment and collaborative representation-based classification with Tikhonov regularization based method (CACRT) is proposed to utilize historical training samples to classify new hyperspectral images. Specifically, the new hyperspectral image and the historical hyperspectral image are preprocessed by spectral matching and covariance alignment. Then the corresponding categories are selected. Finally, using the historical training samples or combined the historical samples with the new labeled samples to classify the new hyperspectral data by CRT classifier. Experimental results prove that the proposed method performs well.

关键词： Training Hyperspectral imaging Cathode ray tubes Testing Collaboration Intserv networks

QoE-Driven Big Data Management in Pervasive Edge Computing Environment

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Big Data Mining and Analytics 2018年第3期1卷 222-233页

作者： Qianyu Meng Kun Wang Xiaoming He Minyi Guo Jiangsu Engineering Research Center of Communication and Network Technology Nanjing University of Posts and Telecommunications Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Nanjing University of Posts and Telecommunications Department of Computer Science and Engineering Shanghai Jiao Tong University Department of Computer Science and Engineering Shanghai Jiao Tong University

In the age of big data, services in the pervasive edge environment are expected to offer end-users better Quality-of-Experience(QoE) than that in a normal edge environment. However, the combined impact of the storage, delivery, and sensors used in various types of edge devices in this environment is producing volumes of high-dimensional big data that are increasingly pervasive and redundant. Therefore, enhancing the QoE has become a major challenge in high-dimensional big data in the pervasive edge computing environment. In this paper, to achieve high QoE, we propose a QoE model for evaluating the qualities of services in the pervasive edge computing environment. The QoE is related to the accuracy of high-dimensional big data and the transmission rate of this accurate data. To realize high accuracy of high-dimensional big data and the transmission of accurate data through out the pervasive edge computing environment, in this study we focused on the following two ***, we formulate the issue as a high-dimensional big data management problem and test different transmission rates to acquire the best QoE. Then, with respect to accuracy, we propose a Tensor-Fast Convolutional Neural Network(TF-CNN) algorithm based on deep learning, which is suitable for high-dimensional big data analysis in the pervasive edge computing environment. Our simulation results reveal that our proposed algorithm can achieve high QoE performance.

关键词： Quality-of-Experience(QoE) high-dimensional big data management deep learning pervasive edge computing

An accuracy-lossless perturbation method for defending privacy attacks in federated learning

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arXiv 2020年

作者： Yang, Xue Feng, Yan Fang, Weijun Shao, Jun Tang, Xiaohu Xia, Shutao Lu, Rongxing Tsinghua Shenzhen International Graduate School Tsinghua University Pcl Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen518055 China School of Computer and Information Engineering Zhejiang Gongshang University Zhejiang310018 China Information Security and National Computing Grid Laboratory Southwest Jiaotong University Chengdu610031 China Canadian Institute of Cybersecurity Faculty of Computer Science University of New Brunswick FrederictonE3B 5A3 Canada

Although federated learning improves privacy of training data by exchanging local gradients or parameters rather than raw data, the adversary still can leverage local gradients and parameters to obtain local training data by launching reconstruction and membership inference attacks. To defend such privacy attacks, many noises perturbation methods (like differential privacy or CountSketch matrix) have been widely designed. However, the strong defence ability and high learning accuracy of these schemes cannot be ensured at the same time, which will impede the wide application of FL in practice (especially for medical or financial institutions that require both high accuracy and strong privacy guarantee). To overcome this issue, in this paper, we propose an efficient model perturbation method for federated learning to defend reconstruction and membership inference attacks launched by curious clients. On the one hand, similar to the differential privacy, our method also selects random numbers as perturbed noises added to the global model parameters, and thus it is very efficient and easy to be integrated in practice. Meanwhile, the random selected noises are positive real numbers and the corresponding value can be arbitrarily large, and thus the strong defence ability can be ensured. On the other hand, unlike differential privacy or other perturbation methods that cannot eliminate the added noises, our method allows the server to recover the true gradients by eliminating the added noises. Therefore, our method does not hinder learning accuracy at all. Extensive experiments demonstrate that for both regression and classification tasks, our method achieves the same accuracy as non-private approaches and outperforms the state-ofthe- art related schemes. Besides, the defence ability of our method is significantly better than the state-of-the-art related defence schemes. Specifically, for the membership inference attack, our method achieves attack success rate (ASR) of aroun

关键词： Perturbation techniques

Strain compensated robust semiconductor saturable absorber mirror for fiber lasers

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Chinese Optics Letters 2019年第7期17卷 59-62页

作者： Yan Wang Nan Lin Wanli Gao Huanyu Song Minglie Hu Haiming Li Wenxia Bao Xiaoyu Ma Zhigang Zhang State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer SciencePeking UniversityBeijing 100871China National Research Center for Optoelectronic Engineering Institute of SemiconductorsChinese Academy of SciencesBeijing 100871China Ultrafast Laser Laboratory Key Laboratory of Opto-electronic Information Technical Science of Ministry of EducationSchool of Precision Instrument and Opto-electronics EngineeringTianjin UniversityTianjin 300072China Huakuai Photonic Technologies Inc. Zhongshan 528400China

We demonstrate a strain compensated long lifetime semiconductor saturable absorber mirror(SESAM) with a high modulation depth for fiber *** SESAM was measured to have a damage threshold of 9.5 m J/cm^2, a modulation depth of 11.5%, a saturation fluence of 39.3 μJ/cm^2, and an inversed saturable absorption coefficient of 630 m J/cm^*** SESAM has been applied to a linear cavity mode-locked Yb-doped fiber laser, which has been working for more than a year without damage of the SESAM.

关键词： Strain robust semiconductor saturable absorber mirror

Privacy-preserving medical treatment system through nondeterministic finite automata

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arXiv 2020年

作者： Yang, Yang Deng, Robert H. Liu, Ximeng Wu, Yongdong Weng, Jian Zheng, Xianghan Rong, Chunming School of Information Systems Singapore Management University Singapore College of Mathematics and Computer Science Fuzhou University Fujian China State Key Laboratory of Integrated Services Networks Xidian University Guangdong Provincial Key Laboratory of Data Security and Privacy Protection Guangzhou China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China School of Information Systems Singapore Management University Singapore Singapore Department of Computer Science Jinan University Guangdong China College of Mathematics and Computer Science Fuzhou University Fujian China Department of Electronic Engineering and Computer Science University of Stavanger Norway MingByte Technology Qingdao China

In this paper, we propose a privacy-preserving medical treatment system using nondeterministic finite automata (NFA), hereafter referred to as P-Med, designed for the remote medical environment. P-Med makes use of the nondeterministic transition characteristic of NFA to flexibly represent the medical model, which includes illness states, treatment methods and state transitions caused by exerting different treatment methods. A medical model is encrypted and outsourced to the cloud to deliver telemedicine services. Using P-Med, patient-centric diagnosis and treatment can be made on-the-fly while protecting the confidentiality of a patient's illness states and treatment recommendation results. Moreover, a new privacy-preserving NFA evaluation method is given in P-Med to get a confidential match result for the evaluation of an encrypted NFA and an encrypted data set, which avoids the cumbersome inner state transition determination. We demonstrate that P-Med realizes treatment procedure recommendation without privacy leakage to unauthorized parties. We conduct extensive experiments and analyses to evaluate efficiency. Copyright © 2020, The Authors. All rights reserved.

关键词： Diseases

Er silicate amplifers and lasers for silicon photonics

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Er silicate amplifers and lasers for silicon photonics

Asia Communications and Photonics Conference

作者： Xingjun Wang Peiqi Zhou Yandong He State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University Beijing 100871 China Institute of Microelectronics School of Electronics Engineering and Computer Science School of Electronics Engineering and Computer Science Peking University Beijing 100871 China

We proposed high performance Er silicate amplifiers and lasers, based on hybrid erbium silicate-silicon nitride strip-loaded waveguides. The results provide supports and guidances for the high performance erbium silic... 详细信息

ISBN: (纸本)9781943580705

关键词： Coupled mode theory Distributed feedback lasers High power lasers Laser amplifiers Optical amplifiers Optical feedback