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arXiv 2023年

作者： Huang, Kai Zhao, Junqiao Zhu, Zhongyang Ye, Chen Feng, Tiantian The School of Surveying and Geo-Informatics Tongji University Shanghai China Department of Computer Science and Technology School of Electronics and Information Engineering Tongji University Shanghai China The MOE Key Lab of Embedded System and Service Computing Tongji University Shanghai China Institute of Intelligent Vehicles Tongji University Shanghai China

Local geometric information, i.e., normal and distribution of points, is crucial for LiDAR-based simultaneous localization and mapping (SLAM) because it provides constraints for data association, which further determines the direction of optimization and ultimately affects the accuracy of localization. However, estimating normal and distribution of points are time-consuming tasks even with the assistance of kdtree or volumetric maps. To achieve fast normal estimation, we look into the structure of LiDAR scan and propose a ring-based fast approximate least squares (Ring FALS) method. With the Ring structural information, estimating the normal requires only the range information of the points when a new scan arrives. To efficiently estimate the distribution of points, we extend the ikd-tree to manage the map in voxels and update the distribution of points in each voxel incrementally while maintaining its consistency with the normal estimation. We further fix the distribution after its convergence to balance the time consumption and the correctness of representation. Based on the extracted and maintained local geometric information, we devise a robust and accurate hierarchical data association scheme where point-to-surfel association is prioritized over point-to-plane. Extensive experiments on diverse public datasets demonstrate the advantages of our system compared to other state-of-the-art methods. Our open source implementation is available at https://***/tiev-tongji/LOG-LIO. Copyright © 2023, The Authors. All rights reserved.

关键词： Optical radar

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LIMOT: A Tightly-Coupled system for LiDAR-Inertial Odometry and Multi-Object Tracking

arXiv

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arXiv 2023年

作者： Zhu, Zhongyang Zhao, Junqiao Huang, Kai Tian, Xuebo Lin, Jiaye Ye, Chen Department of Computer Science and Technology School of Electronics and Information Engineering Tongji University Shanghai China The MOE Key Lab of Embedded System and Service Computing Tongji University Shanghai China Institute of Intelligent Vehicles Tongji University Shanghai China The School of Surveying and Geo-Informatics Tongji University Shanghai China

Simultaneous localization and mapping (SLAM) is critical to the implementation of autonomous driving. Most LiDAR-inertial SLAM algorithms assume a static environment, leading to unreliable localization in dynamic environments. Moreover, the accurate tracking of moving objects is of great significance for the control and planning of autonomous vehicles. This study proposes LIMOT, a tightly-coupled multi-object tracking and LiDAR-inertial odometry system that is capable of accurately estimating the poses of both ego-vehicle and objects. We propose a trajectory-based dynamic feature filtering method, which filters out features belonging to moving objects by leveraging tracking results before scan-matching. Factor graph-based optimization is then conducted to optimize the bias of the IMU and the poses of both the ego-vehicle and surrounding objects in a sliding window. Experiments conducted on the KITTI tracking dataset and self-collected dataset show that our method achieves better pose and tracking accuracy than our previous work DL-SLOT and other baseline methods. Our open-source implementation is available at https://***/tiev-tongji/LIMOT. Copyright © 2023, The Authors. All rights reserved.

关键词： Autonomous vehicles

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Learning Sequence Descriptor based on Spatio-Temporal Attention for Visual Place Recognition

arXiv

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arXiv 2023年

作者： Zhao, Junqiao Zhang, Fenglin Cai, Yingfeng Tian, Gengxuan Mu, Wenjie Ye, Chen Feng, Tiantian Department of Computer Science and Technology School of Electronics and Information Engineering Tongji University Shanghai China The MOE Key Lab of Embedded System and Service Computing Tongji University Shanghai China Institute of Intelligent Vehicles Tongji University Shanghai China School of Surveying and Geo-Informatics Tongji University Shanghai China

Visual Place Recognition (VPR) aims to retrieve frames from a geotagged database that are located at the same place as the query frame. To improve the robustness of VPR in perceptually aliasing scenarios, sequence-based VPR methods are proposed. These methods are either based on matching between frame sequences or extracting sequence descriptors for direct retrieval. However, the former is usually based on the assumption of constant velocity, which is difficult to hold in practice, and is computationally expensive and subject to sequence length. Although the latter overcomes these problems, existing sequence descriptors are constructed by aggregating features of multiple frames only, without interaction on temporal information, and thus cannot obtain descriptors with spatio-temporal discrimination. In this paper, we propose a sequence descriptor that effectively incorporates spatio-temporal information. Specifically, spatial attention within the same frame is utilized to learn spatial feature patterns, while attention in corresponding local regions of different frames is utilized to learn the persistence or change of features over time. We use a sliding window to control the temporal range of attention and use relative positional encoding to construct sequential relationships between different features. This allows our descriptors to capture the intrinsic dynamics in a sequence of frames. Comprehensive experiments on challenging benchmark datasets show that the proposed approach outperforms recent state-of-the-art methods. The code is available at https://***/tiev-tongji/Spatio-Temporal-SeqVPR. Copyright © 2023, The Authors. All rights reserved.

关键词： Query processing

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A deep learning system for predicting time to progression of diabetic retinopathy

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NATURE MEDICINE 2024年第2期30卷 358-359页

作者： [Anonymous] Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders Department of Computer Science and Engineering School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Department of Endocrinology and Metabolism Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai Diabetes Institute Shanghai Clinical Center for Diabetes Shanghai China MOE Key Laboratory of AI School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Department of Ophthalmology Huadong Sanatorium Wuxi China Department of Ophthalmology Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai China Department of Ophthalmology and Visual Sciences The Chinese University of Hong Kong Hong Kong China Singapore Eye Research Institute Singapore National Eye Centre Singapore Singapore Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong China Department of Chemical and Biological Engineering The Hong Kong University of Science and Technology Hong Kong China State Key Laboratory of Ophthalmology Zhongshan Ophthalmic Center Sun Yat-sen University Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science Guangzhou China Department of Ophthalmology Peking Union Medical College Hospital Peking Union Medical College Chinese Academy of Medical Sciences Beijing China Medical Records and Statistics Office Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai China Department of Geriatrics Tongji Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan China National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Tech

We developed and validated a deep learning system (termed DeepDR Plus) in a diverse, multiethnic, multi-country dataset to predict personalized risk and time to progression of diabetic retinopathy. We show that DeepDR Plus can be integrated into the clinical workflow to promote individualized intervention strategies for the management of diabetic retinopathy.

关键词： Diabetes complications Machine learning Predictive markers

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A transactional-behavior-based hierarchical gated network for credit card fraud detection

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IEEE/CAA Journal of Automatica Sinica 2025年

作者： Xie, Yu Zhou, MengChu Liu, Guanjun Wei, Lifei Zhu, Honghao De Meo, Pasquale College of Information Engineering Shanghai Maritime University Shanghai201306 China School of Information and Electronic Engineering Zhejiang Gongshang University Hangzhou310018 China Helen and John C. Hartmann Department of Electrical and Computer Engineering New Jersey Institute of Technology NewarkNJ07102 United States Key Laboratory of Embedded System and Service Computing Ministry of Education Department of Computer Science Tongji University Shanghai201804 China College of Computer Science and Information Engineering Bengbu University Bengbu233030 China Department of Ancient and Modern Civilizations University of Messina Messina98166 Italy

The task of detecting fraud in credit card transactions is crucial to ensure the security and stability of a financial system, as well as to enforce customer confidence in digital payment systems. Historically, credit card companies have used rule-based approaches to detect fraudulent transactions, but these have proven inadequate due to the complexity of fraud strategies and have been replaced by much more powerful solutions based on machine learning or deep learning algorithms. Despite significant progress, the current approaches to fraud detection suffer from a number of limitations: for example, it is unclear whether some transaction features are more effective than others in discriminating fraudulent transactions, and they often neglect possible correlations among transactions, even though they could reveal illicit behaviour. In this paper, we propose a novel credit card fraud detection (CCFD) method based on a transaction behaviour-based hierarchical gated network. First, we introduce a feature-oriented extraction module capable of identifying key features from original transactions, and such analysis is effective in revealing the behavioural characteristics of fraudsters. Second, we design a transaction-oriented extraction module capable of capturing the correlation between users' historical and current transactional behaviour. Such information is crucial for revealing users' sequential behaviour patterns. Our approach, called transactional-behaviour-based hierarchical gated network model (TbHGN), extracts two types of new transactional features, which are then combined in a feature interaction module to learn the final transactional representations used for CCFD. We have conducted extensive experiments on a real-world credit card transaction dataset with an increase in average F1 between 1.42% and 6.53% and an improvement in average AUC between 0.63% and 2.78% over the state of the art. © 2025 Institute of Electrical and electronics Engineers Inc.. All right

关键词： Deep learning

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Fully implantable and battery-free wireless optoelectronic system for modulable cancer therapy and real-time monitoring

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npj Flexible electronics 2023年第1期7卷 119-130页

作者： Kiho Kim In Sik Min Tae Hee Kim Do Hyeon Kim Seungwon Hwang Kyowon Kang Kyubeen Kim Sangun Park Jongmin Lee Young Uk Cho Jung Woo Lee Woon-Hong Yeo Young Min Song Youngmee Jung Ki Jun Yu Functional Bio-integrated Electronics and Energy Management Lab School of Electrical and Electronic EngineeringYonsei University50 Yonsei-roSeodaemun-guSeoul 03722Republic of Korea Center for Biomaterials Biomedical Research InstituteKorea Institute of Science and Technology(KIST)Seoul 02792Republic of Korea Department of Fusion Research and Collaboration Biomedical Research InstituteSeoul National University HospitalSeoul 03080Republic of Korea School of Electrical Engineering and Computer Science(EECS) Gwangju Institute of Science and Technology(GIST)Gwangju 61005Republic of Korea PA1 Foundry BusinessSamsung Electronics1 Samsungjeonja-roHwaseong-siGyeonggi-doRepublic of Korea R&D Center DNA Lab PharmaresearchSeongnam 13486Republic of Korea KU-KIST Graduate School of Converging Science and Technology Korea UniversitySeoul 136-705Republic of Korea School of Materials Science and Engineering Energy Materials for Soft Electronics LaboratoryPusan National UniversityBusan 46241Republic of Korea IEN Center for Human-Centric Interfaces and Engineering and George W.Woodruff School of Mechanical Engineering Georgia Institute of TechnologyAtlantaGA 30332USA Wallace H.Coulter Department of Biomedical Engineering Georgia Institute of Technology and Emory University School of MedicineAtlantaGA 30332USA Institute for Robotics and Intelligent Machines Parker H.Petit Institute for Bioengineering and BiosciencesInstitute for MaterialsNeural Engineering CenterGeorgia Institute of TechnologyAtlantaGA 30332USA School of Electrical and Electronic Engineering YU-Korea Institute of Science and Technology(KIST)InstituteYonsei University50Yonsei-roSeodaemun-guSeoul 03722Republic of Korea

Photodynamic therapy(PDT)is attracting attention as a next-generation cancer treatment that can selectively destroy malignant tissues,exhibit fewer side effects,and lack pain during *** PDT systems have recently been developed to resolve the issues of bulky and expensive conventional PDT systems and to implement continuous and repetitive *** implantable PDT systems,however,are not able to perform multiple functions simultaneously,such as modulating light intensity,measuring,and transmitting tumor-related data,resulting in the complexity of cancer ***,we introduce a flexible and fully implantable wireless optoelectronic system capable of continuous and effective cancer treatment by fusing PDT and hyperthermia and enabling tumor size monitoring in *** system exploits micro inorganic light-emitting diodes(μ-LED)that emit light with a wavelength of 624 nm,designed not to affect surrounding normal tissues by utilizing a fully programmable light intensity ofμ-LED and precisely monitoring the tumor size by Si phototransistor during a long-term implantation(2–3 weeks).The superiority of simultaneous cancer treatment and tumor size monitoring capabilities of our system operated by wireless power and data transmissions with a cell phone was confirmed through in vitro experiments,ray-tracing simulation results,and a tumor xenograft mouse model in *** all-in-one single system for cancer treatment offers opportunities to not only enable effective treatment of tumors located deep in the tissue but also enable precise and continuous monitoring of tumor size in real-time.

关键词： optoelectronic enable battery

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Deep Feature Surgery: Towards Accurate and Efficient Multi-Exit Networks

arXiv

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arXiv 2024年

作者： Gong, Cheng Chen, Yao Luo, Qiuyang Lu, Ye Li, Tao Zhang, Yuzhi Sun, Yufei Zhang, Le College of Software Nankai University China College of Computer Science Nankai University China National University of Singapore Singapore School of Information and Communication Engineering University of Electronic Science and Technology of China China HAIHE Lab of ITAI China Tianjin Key Laboratory of Network and Data Security Technology China Key Laboratory of Data and Intelligent System Security Ministry of Education

Multi-exit network is a promising architecture for efficient model inference by sharing backbone networks and weights among multiple exits. However, the gradient conflict of the shared weights results in sub-optimal accuracy. This paper introduces Deep Feature Surgery (DFS), which consists of feature partitioning and feature referencing approaches to resolve gradient conflict issues during the training of multi-exit networks. The feature partitioning separates shared features along the depth axis among all exits to alleviate gradient conflict while simultaneously promoting joint optimization for each exit. Subsequently, feature referencing enhances multi-scale features for distinct exits across varying depths to improve the model accuracy. Furthermore, DFS reduces the training operations with the reduced complexity of backpropagation. Experimental results on Cifar100 and ImageNet datasets exhibit that DFS provides up to a 50.00% reduction in training time and attains up to a 6.94% enhancement in accuracy when contrasted with baseline methods across diverse models and tasks. Budgeted batch classification evaluation on MSDNet demonstrates that DFS uses about 2× fewer average FLOPs per image to achieve the same classification accuracy as baseline methods on Cifar100. The code is available at https: //***/GongCheng1919/dfs. Copyright © 2024, The Authors. All rights reserved.

关键词： Budget control

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Scalar optical hopfions

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eLight 2022年第1期2卷 284-290页

作者： Chenhao Wan Yijie Shen Andy Chong Qiwen Zhan School of Optical‑Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China School of Optical and Electronic Information and Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan 430074HubeiChina Optoelectronics Research Centre University of SouthamptonSouthampton SO171BJUK Department of Physics Pusan National UniversityGeumjeong‑GuBusan 46241South Korea Zhangjiang Laboratory 100 Haike RoadShanghai 201204China Shanghai Key Lab of Modern Optical System University of Shanghai for Science and TechnologyShanghai 200093China

Hopfions are three-dimensional(3D)topological states discovered in field theory,magnetics,and hydrodynamics that resemble particle-like objects in physical *** inherit the topological features of the Hopf fibration,a homotopic mapping from unit sphere in 4D space to unit sphere in 3D *** we design and demonstrate dynamic scalar optical hopfions in the shape of a toroidal vortex and expressed as an approximate solution to Maxwell’s *** lines correspond to disjoint and interlinked loops forming complete ring tori in 3D *** Hopf invariant,product of two winding numbers,is determined by the topological charge of the poloidal spatiotemporal vortices and toroidal spatial vortices in toroidal *** hopfions provide a photonic testbed for studying topological states and may be utilized as high-dimensional information carriers.

关键词： Hopfion Toroidal vortex Spatiotemporal vortex Wave packet Topology Topological charge

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Protected Health Information Recognition of Unstructured Code-Mixed electronic Health Records in Taiwan 18

Protected Health Information Recognition of Unstructured Cod...

引用

18th World Congress on Medical and Health Informatics: One World, One Health - Global Partnership for Digital Innovation, MEDINFO 2021

作者： Lee, You-Qian Wang, Bo-Hong Su, Chu-Hsien Chen, Pei-Tsz Lin, Wu-Qing Wu, Chi-Shin Dai, Hong-Jie Intelligent System Lab College of Electrical Engineering and Computer Science Department of Electrical Engineering National Kaohsiung University Science and Technology Kaohsiung Taiwan Department of Psychiatry National Taiwan University Hospital Taipei Taiwan Department of Chemical Engineering Feng Chia University Taichung Taiwan National Institute of Cancer Research National Health Research Institutes Tainan Taiwan School of Post-Baccalaureate Medicine Kaohsiung Medical University Kaohsiung Taiwan

ISBN: (纸本)9781643682648

electronic health records (EHRs) at medical institutions provide valuable sources for research in both clinical and biomedical domains. However, before such records can be used for research purposes, protected health information (PHI) mentioned in the unstructured text must be removed. In Taiwan's EHR systems the unstructured EHR texts are usually represented in the mixing of English and Chinese languages, which brings challenges for de-identification. This paper presented the first study, to the best of our knowledge, of the construction of a code-mixed EHR de-identification corpus and the evaluation of different mature entity recognition methods applied for the code-mixed PHI recognition task. © 2022 International Medical Informatics Association (IMIA) and IOS Press.

关键词： Mixing

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Reshaping the ISAC Tradeoff Under OFDM Signaling: A Probabilistic Constellation Shaping Approach

arXiv

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arXiv 2023年

作者： Du, Zhen Liu, Fan Xiong, Yifeng Han, Tony Xiao Eldar, Yonina C. Jin, Shi The School of Electronic and Information Engineering Nanjing University of Information Science and Technology Nanjing China School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China The School of Information and Electronic Engineering Beijing University of Posts and Telecommunications Beijing China Huawei Technologies Co. Ltd Shenzhen China The Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot Israel National Mobile Communications Research Laboratory Southeast University Nanjing210096 China

Integrated sensing and communications is regarded as a key enabling technology in the sixth generation networks, where a unified waveform, such as orthogonal frequency division multiplexing (OFDM) signal, is adopted to facilitate both sensing and communications (S&C). However, the random communication data embedded in the OFDM signal results in severe variability in the sidelobes of its ambiguity function (AF), which leads to missed detection of weak targets and false detection of ghost targets, thereby impairing the sensing performance. Therefore, balancing between preserving communication capability (i.e., the randomness) while improving sensing performance remains a challenging task. To cope with this issue, we characterize the random AF of OFDM communication signals, and demonstrate that the AF variance is determined by the fourth-moment of the constellation amplitudes. Subsequently, we propose an optimal probabilistic constellation shaping (PCS) approach by maximizing the achievable information rate (AIR) under the fourth-moment, power and probability constraints, where the optimal input distribution may be numerically specified through a modified Blahut-Arimoto algorithm. To reduce the computational overheads, we further propose a heuristic PCS approach by actively controlling the value of the fourth-moment, without involving the communication metric in the optimization model, despite that the AIR is passively scaled with the variation of the input distribution. Numerical results show that both approaches strike a scalable performance tradeoff between S&C, where the superiority of the PCS-enabled constellations over conventional uniform constellations is also verified. Notably, the heuristic approach achieves very close performance to the optimal counterpart, at a much lower computational complexity. Copyright © 2023, The Authors. All rights reserved.

关键词： Orthogonal frequency division multiplexing

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