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IEEE Workshop on Applications of Computer Vision (WACV)

作者： Wenxin Ma Qingsong Yao Xiang Zhang Zhelong Huang Zihang Jiang S. Kevin Zhou Division of Life Sciences and Medicine School of Biomedical Engineering University of Science and Technology of China (USTC) Hefei Anhui China Center for Medical Imaging Robotics Analytic Computing & Learning (MIRACLE) USTC Suzhou Institute for Advance Research Suzhou Jiangsu China Stanford University Palo Alto California United State School of Medicine Shanghai University Shanghai China Key Laboratory of Precision and Intelligent Chemistry USTC Hefei Anhui China Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS

ISBN: (数字)9798331510831

ISBN: (纸本)9798331510848

Unsupervised anomaly detection (UAD) from images strives to model normal data distributions, creating discriminative representations to distinguish and precisely localize anomalies. Despite recent advancements in the efficient and unified one-for-all scheme, challenges persist in accurately segmenting anomalies for further monitoring. Moreover, this problem is obscured by the widely-used AUROC metric under imbalanced UAD settings. This motivates us to emphasize the significance of precise segmentation of anomaly pixels using pAP and DSC as metrics. To address the unsolved segmentation task, we introduce the Unified Anomaly Segmentation (UniAS). UniAS presents a multi-level hybrid pipeline that progressively enhances normal information from coarse to fine, incorporating a novel multi-granularity gated CNN (MGG-CNN) into Transformer layers to explicitly aggregate local details from different granularities. UniAS achieves state-of-the-art anomaly segmentation performance, attaining 65.12/59.33 and 40.06/32.50 in pAP/DSC on the MVTec-AD and VisA datasets, respectively, surpassing previous methods significantly. The codes are shared at https://***/Mwxinnn/UniAS.

关键词： Measurement Image segmentation Computer vision Codes Pipelines Logic gates Transformers Data models Monitoring Anomaly detection

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Modeling and Coverage Analysis of RIS-assisted Integrated Sensing and communication Networks

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IEEE Transactions on Wireless communications 2025年

作者： Gan, Xu Huang, Chongwen Yang, Zhaohui Chen, Xiaoming Bader, Faouzi Zhang, Zhaoyang Yuen, Chau Guan, Yong Liang Debbah, Merouane Zhejiang University College of Information Science and Electronic Engineering Hangzhou310027 China Xidian University State Key Laboratory of Integrated Service Networks Xian710071 China Zhejiang Provincial Key Laboratory of Multi-Modal Communication Networks and Intelligent Information Processing Hangzhou310027 China Nord Europe Lille France Nanyang Technological University School of Electrical and Electronics Engineering 639798 Singapore Khalifa University of Science and Technology KU6G Research Center PO Box 127788 Abu Dhabi United Arab Emirates University Paris-Saclay CentraleSupelec Gif-sur-Yvette91192 France

Integrated sensing and communication (ISAC) has emerged as a promising technology to facilitate high-rate communications and super-resolution sensing, particularly operating in the millimeter wave (mmWave) band. However, the vulnerability of mmWave signals to blockages severely impairs ISAC capabilities and coverage. To tackle this, an efficient and low-cost solution is to deploy distributed reconfigurable intelligent surfaces (RISs) to construct virtual links between the base stations (BSs) and users in a controllable fashion. In this paper, we model the generalized RIS-assisted mmWave ISAC networks considering the blockage effect, and examine the beneficial impact of RISs on the coverage rate utilizing stochastic geometry. Based on the proposed beam patterns and user association policies, we derive the conditional coverage probability and ergodic rate of communication and sensing dual functions for two association cases, as well as the marginal coverage rate using the distance-dependent thinning method. Taking into account the coupling effect of ISAC dual functions within the same network topology, we further calculate the joint coverage probability of ISAC performance. Simulation results verify the accuracy of derived theoretical formulations, and illustrate the impact of the RIS aperture, blockage, BS and RIS densities on ISAC coverage rates, which provide valuable guidelines for the practical network deployment. Specifically, our results indicate the superiority of the RIS deployment with the density of 40 km-2 BSs, and that the joint coverage rate of ISAC performance exhibits potential growth from 62% to 97% with the deployment of RISs. © 2025 IEEE.

关键词： Network topology

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Diffie-Hellman key exchange protocol based on ring-LWE

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Open Cybernetics and Systemics Journal 2015年第1期9卷 1033-1037页

作者： Zhi-Min, Yu Zheng-Jun, Jing Shi-Cun, Li Key Laboratory of Cloud Computing and Intelligent Information Processing of Changzhou City Jiangsu University of Technology ChangzhouJiangsu213001 China

In this paper, we first construct a one-round Diffie-Hellman key exchange protocol based on Ring-LWE. The security of our construction is based on the hardness of the Ring-LWE problem. Second, we adaptively extend our construction from Ring-LWE to LWE. Finally, we efficiently implement our key exchange protocols based on Ring-LWE and LWE. © Zhi-Min et al.

关键词： Diffie-Hellman key exchange LWE ring-LWE security

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Selective Visual Relationship Detection with Adaptive Context Learning 17

Selective Visual Relationship Detection with Adaptive Contex...

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17th International Congress on Image and Signal processing, BioMedical Engineering and Informatics, CISP-BMEI 2024

作者： Tu, Jiangwei Liu, Feng Nanjing University of Posts and Telecommunications Jiangsu Key Laboratory of Intelligent Information Processing and Communication Technology Nanjing China

ISBN: (纸本)9798331507398

Visual relation detection aims to describe the relationships between objects in a scene by using the form of a triplet . Existing methods not only suffer from the huge number of combinations of triples, but also make the context of most of the object pairs in a scene non-discriminative due to simply using the union box of the object pair. In this work, we propose a novel two-stage network. In the first stage, the multi-modal feature fusion strategy is used to complete the correlation detection of object pairs, which reduces the number of triples and enables the model to selectively focus on the relationship between strongly correlated objects in the scene. The object-directed context module (OCM) and global message passing (GMP) introduced in the second stage to adaptively learning the higher-order context of each object pair in the scenario. We evaluate our method on two widely used datasets: Visual Relationship Detection (VRD) and Visual Genome(VG) datasets. Experimental results verify the effectiveness of our method, e.g., the top 100 phrases detection recall improves from 40.01% to 41.21% on the VRD dataset. © 2024 IEEE.

关键词： Contrastive Learning

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Prominent Edge Characteristics for Open World Object Detection 17

Prominent Edge Characteristics for Open World Object Detecti...

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17th International Congress on Image and Signal processing, BioMedical Engineering and Informatics, CISP-BMEI 2024

作者： Li, Shihao Liu, Feng Nanjing University of Posts and Telecommunications Jiangsu Key Laboratory of Intelligent Information Processing and Communication Technology Nanjing China

ISBN: (纸本)9798331507398

Open world object detection aims to simulate the human process of recognizing objects in real life scenarios. It can identify categories not introduced during the training phase as unknown during the testing phase and recognize these unknowns in subsequent incremental learning. This capability is beyond the reach of traditional object detection, making it closer to real world human experiences and thus garnering significant attention from researchers. However, existing studies largely focus on generating better pseudo labels to improve the recall rate of unknown objects, which evidently neglects the intrinsic differences between objects and backgrounds. Considering important information such as the visual saliency and edge features of objects in realistic scenes, this paper proposes a novel solution called PEC, which directly extracts objects from their background to detect known and unknown objects more accurately. Comprehensive experiments on the M-OWODB benchmark demonstrate that our method outperforms other current mainstream approaches. © 2024 IEEE.

关键词： edge attention object detection open world unknown object recognition

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The M-computations induced by accessibility relations in nonstandard models M of Hoare logic

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Frontiers of Computer Science 2016年第4期10卷 717-725页

作者： Cungen CAO Yuefei SUI Zaiyue ZHANG Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Department of Computer Science Jiangsu University of Sciences and Technology Zhenjiang 212003 China

Hoare logic is a logic used as a way of specifying semantics of programming languages, which has been extended to be a separation logic to reason about mutable heap structure. In a model M of Hoare logic, each program α induces an M-computable function fα M on the universe of M; and the M-recursive functions are defined on M. It will be proved that the class of all the M-computable functions fα M induced by programs is equal to the class of all the M- recursive functions. Moreover, each M-recursive function is ∑ 1 NM -definable in M, where the universal quantifier is a num- ber quantifier ranging over the standard part of a nonstandard model M.

关键词： Hoare logic recursive :Function computable function nonstandard model of Peano arithmetic

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LMP-GAN: Out-Of-Distribution Detection For Non-Control Data Malware Attacks

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IEEE Transactions on Pattern Analysis and Machine Intelligence 2025年 PP卷 PP页

作者： Wood, David Kapp, David Kebede, Temesgen Hirakawa, Keigo Wuhan University School of Computer Science China Wuhan University National Engineering Research Center for Multimedia Software Hubei Key Laboratory of Multimedia and Network Communication Engineering China Zhongguancun Academy China Wuhan University State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing China Sun Yat-sen University School of Geography and Planning China Mohamed bin Zayed University of Artificial Intelligence United Arab Emirates Chongqing University College of Computer Science China The University of Tokyo Japan RIKEN Center for Advanced Intelligence Project Japan Intelligent Science & Technology Academy Limited CASIC China iFlytek Company Ltd. National Engineering Research Center of Speech and Language Information Processing China Nanyang Technological University College of Computing & Data Science Singapore Henan Academy of Sciences Aerospace Information Research Institute China

Anomaly detection is a common application of machine learning. Out-of-distribution (OOD) detection in particular is a semi-supervised anomaly detection technique where the detection method is trained only on the inlier (in-distribution) samples - unlike the fully supervised variant, the distribution of the outlier samples are never explicitly modeled in OOD detection tasks. In this work, we design a novel GAN-based OOD detection network specifically designed to protect a cyber-physical signal systems from novel Trojan malware called non-control data (NCD) attack that evades conventional malware detection techniques. Inspired in part by the classical locally most powerful (LMP) test in statistical inferences, the proposed LMP-GAN trains the OOD detector (discriminator) by generating OOD samples that are aimed at making maximal alteration to the inlier samples while evading detection. We experimentally compare the results to the state-of-the-art anomaly detection methods to demonstrate the benefits and the appropriateness of the LMP-GAN OOD detector. © 2025 IEEE.

关键词： Malware

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Weak value amplification via second-order correlated technique

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Chinese Physics B 2016年第2期25卷 58-61页

作者：崔挺黄靖正刘翔曾贵华 State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Key Laboratory on Navigation and Location-based Serviceand Center of Quantum Information Sensing and Processing Shanghai Jiao Tong University Shanghai Key Laboratory of Aerospace Intelligent Control Technology Shanghai Institute of Spaceflight Control Technology College of Information Science and Technology Northwest University

We propose a new framework combining weak measurement and second-order correlated technique. The theoretical analysis shows that weak value amplification （WVA） experiment can also be implemented by a second-order correlated system. We then build two-dimensional second-order correlated function patterns for achieving higher amplification factor and discuss the signal-to-noise ratio influence. Several advantages can be obtained by our proposal. For instance, detectors with high resolution are not necessary. Moreover, detectors with low saturation intensity are available in WVA setup. Finally, type-one technical noise can be effectively suppressed.

关键词： weak measurement two-dimensional second-order correlated function

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Privacy preservation in role-based access control model

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Journal of Networks 2011年第8期6卷 1106-1113页

作者： Chen, Zuo Yang, Qiuwei Wan, Xin Tu, Yuanyan Yu, Fei Xu, Chen School of Computer and Communication Hunan University Changsha China Jiangsu Provincial Key Laboratory for Computer Information Processing Technology Soochow University Soochow China

Privacy preservation is a crucial problem in resource sharing and collaborating among multi-domains. Based on this problem, we propose a role-based access control model for privacy preservation. This scheme avoided the privacy leakage of resources while implementing access control, and it has the advantage of lower communication overhead. We demonstrate this scheme meets the IND-CCA2 semantic security by using random oracle. The simulation result shows this scheme has better execution efficiency and application effects. © 2011 ACADEMY PUBLISHER.

关键词： Cryptography

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Automated trust negotiation with time behavior

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Journal of Networks 2011年第8期6卷 1091-1098页

作者： Chen, Zuo Yang, Qiuwei Wan, Xin Tu, Yuanyan Yu, Fei Xu, Chen School of Computer and Communication Hunan University Chang sha China Jiangsu Provincial Key Laboratory for Computer Information Processing Technology Soochow University Soochow China

In automated trust negotiation(ATN), strangers build trust relationship by disclosing attributes credentials alternately. In the recent study of ATN, there was no rigorous formal definition of ATN abstract model, and have nothing to do with the time behavior. It exist denial of service attack which can lead system to paralysis. We present the basic components of ATN abstract model. It defines ATN abstract model by bringing state-transition system. Based on this formalized basis, the time behavior will be explored. We analyze and discuss some time semantics of ATN, and describe the extended ATN by constructing a state-transition system with time behavior. It can describe the ATN abstract model more comprehensive and secure. The satiability of security policies in ATN is discussed. © 2011 ACADEMY PUBLISHER.

关键词： Denial-of-service attack

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