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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Zhou, Ziqi Song, Yufei Li, Minghui Hu, Shengshan Wang, Xianlong Zhang, Leo Yu Yao, Dezhong Jin, Hai National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab China Cluster and Grid Computing Lab China Hubei Engineering Research Center on Big Data Security China Hubei Key Laboratory of Distributed System Security China School of Computer Science and Technology Huazhong University of Science and Technology China School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Software Engineering Huazhong University of Science and Technology China School of Information and Communication Technology Griffith University Australia

Segment Anything Model (SAM) has recently gained much attention for its outstanding generalization to unseen data and tasks. Despite its promising prospect, the vulnerabilities of SAM, especially to universal adversarial perturbation (UAP) have not been thoroughly investigated yet. In this paper, we propose DarkSAM, the first prompt-free universal attack framework against SAM, including a semantic decoupling-based spatial attack and a texture distortion-based frequency attack. We first divide the output of SAM into foreground and background. Then, we design a shadow target strategy to obtain the semantic blueprint of the image as the attack target. DarkSAM is dedicated to fooling SAM by extracting and destroying crucial object features from images in both spatial and frequency domains. In the spatial domain, we disrupt the semantics of both the foreground and background in the image to confuse SAM. In the frequency domain, we further enhance the attack effectiveness by distorting the high-frequency components (i.e., texture information) of the image. Consequently, with a single UAP, DarkSAM renders SAM incapable of segmenting objects across diverse images with varying prompts. Experimental results on four datasets for SAM and its two variant models demonstrate the powerful attack capability and transferability of DarkSAM. Our codes are available at: https://***/CGCL-codes/DarkSAM. © 2024 Neural information processing systems foundation. All rights reserved.

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SEPT: Standard-Definition Map Enhanced Scene Perception and Topology Reasoning for Autonomous Driving

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IEEE Robotics and Automation Letters 2025年第7期10卷 7126-7133页

作者： Pei, Muleilan Shan, Jiayao Li, Peiliang Shi, Jieqi Huo, Jing Gao, Yang Shen, Shaojie Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong Zhuoyu Technology Shenzhen China Nanjing University State Key Laboratory for Novel Software Technology Nanjing China

Online scene perception and topology reasoning are critical for autonomous vehicles to understand their driving environments, particularly for mapless driving systems that endeavor to reduce reliance on costly High-Definition (HD) maps. However, recent advances in online scene understanding still face limitations, especially in long-range or occluded scenarios, due to the inherent constraints of onboard sensors. To address this challenge, we propose a Standard-Definition (SD) Map Enhanced scene Perception and Topology reasoning (SEPT) framework, which explores how to effectively incorporate the SD map as prior knowledge into existing perception and reasoning pipelines. Specifically, we introduce a novel hybrid feature fusion strategy that combines SD maps with Bird's-Eye-View (BEV) features, considering both rasterized and vectorized representations, while mitigating potential misalignment between SD maps and BEV feature spaces. Additionally, we leverage the SD map characteristics to design an auxiliary intersection-aware keypoint detection task, which further enhances the overall scene understanding performance. Experimental results on the large-scale OpenLane-V2 dataset demonstrate that by effectively integrating SD map priors, our framework significantly improves both scene perception and topology reasoning, outperforming existing methods by a substantial margin. 2016 IEEE.

关键词： Deep learning

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A Hybrid Vectorized Merge Sort on ARM NEON 24th

A Hybrid Vectorized Merge Sort on ARM NEON

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24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

作者： Zhou, Jincheng Zhang, Jin Zhang, Xiang Xiao, Tiaojie Ma, Di Gong, Chunye School of Computer and Communication Engineering Changsha University of Science and Technology Changsha410114 China College of Computer National University of Defense Technology Hunan Changsha410073 China Laboratory of Digitizing Software for Frontier Equipment National University of Defense Technology Changsha410073 China National Supercomputer Center in Tianjin Tianjin300457 China

ISBN: (纸本)9789819615506

Sorting algorithms are the most extensively researched topics in computer science and serve for numerous practical applications. Although various sorts have been proposed for efficiency, different architectures offer distinct flavors to the implementation of parallel sorting. In this paper, we propose a hybrid vectorized merge sort on ARM NEON, named NEON Merge Sort for short (NEON-MS). In detail, according to the granted register functions, we first identify the optimal register number to avoid the register-to-memory access, due to the write-back of intermediate outcomes. More importantly, following the generic merge sort framework that primarily uses sorting network for column sort and merging networks for three types of vectorized merge, we further improve their structures for high efficiency in an unified asymmetry way: 1) it makes the optimal sorting networks with few comparators become possible;2) hybrid implementation of both serial and vectorized merges incurs the pipeline with merge instructions highly interleaved. Experiments on a single FT2000+ core show that NEON-MS is 3.8 and 2.1 times faster than std::sort and boost::block_sort, respectively, on average. Additionally, as compared to the parallel version of the latter, NEON-MS gains an average speedup of 1.25. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Memory architecture

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Driving Scene Understanding with Traffic Scene-Assisted Topology Graph Transformer 24

Driving Scene Understanding with Traffic Scene-Assisted Topo...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Rong, Fu Peng, Wenjin Lan, Meng Zhang, Qian Zhang, Lefei National Engineering Research Center for Multimedia Software School of Computer Science Wuhan University Wuhan China School of Cyber Science and Engineering Wuhan University Wuhan China Hong Kong University of Science and Technology Hong Kong Hong Kong Horizon Robotics Beijing China National Engineering Research Center for Multimedia Software School of Computer Science Wuhan University Hubei Luojia Laboratory Wuhan China

ISBN: (纸本)9798400706868

Driving scene topology reasoning aims to understand the objects present in the current road scene and model their topology relationships to provide guidance information for downstream tasks. Previous approaches fail to adequately facilitate interactions among traffic objects and neglect to incorporate scene information into topology reasoning, thus limiting the comprehensive exploration of potential correlations among objects and diminishing the practical significance of the reasoning results. Besides, the lack of constraints on lane direction may introduce erroneous guidance information and lead to a decrease in topology prediction accuracy. In this paper, we propose a novel topology reasoning framework, dubbed TSTGT, to address these issues. Specifically, we design a divide-and-conquer topology graph Transformer to respectively infer the lane-lane and lane-traffic topology relationships, which can effectively aggregate the local and global object information in the driving scene and facilitate the topology relationship learning. Additionally, a traffic scene-assisted reasoning module is devised and combined with the topology graph Transformer to enhance the practical significance of lane-traffic topology. In terms of lane detection, we develop a point-wise matching strategy to infer lane centerlines with correct directions, thereby improving the topology reasoning accuracy. Extensive experimental results on Openlane-V2 benchmark validate the superiority of our TSTGT over state-of-the-art methods and the effectiveness of our proposed modules. The code is available at https://***/rongfu-dsb/TSTGT. © 2024 ACM.

关键词： Graph theory

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Distributed Feature Reduction Signal Sorting Algorithm

Distributed Feature Reduction Signal Sorting Algorithm

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International Conference on Guidance, Navigation and Control, ICGNC 2022

作者： Wan, Liangtian Wang, Jinjing Sun, Lu Wang, Xianpeng Lu, Cunbo Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province School of Software Dalian University of Technology Dalian116620 China Department of Communication Engineering Institute of Information Science Technology Dalian Maritime University Dalian116026 China School of Information and Communication Engineering Hainan University Haikou570228 China Information Science Academy China Electronics Technology Group Corporation Beijing100098 China

ISBN: (纸本)9789811966125

With the development of science and technology, modern war has changed from traditional mechanized war to electronic war. Electronic warfare has become the mainstream combat mode in modern war. At present, the electromagnetic environment is very chaotic and complex, the pulse density increases rapidly, and the pulse modulation mode is complex and changeable. In order to deal with the low efficiency of traditional methods in complex electromagnetic environment, a distributed feature reduction signal sorting method is proposed. Firstly, attribute entropy regularization is added to the objective function, and different weights are given to different features. Secondly, the feature reduction process is added to select which dimension of features to be discarded by setting the threshold. Each iteration of the algorithm will update the membership matrix, cluster center and feature weight matrix until the termination conditions is satisfied. Simulation results show that the algorithm can reduce the number of iterations and time, and improve the accuracy of radar signal sorting results by reducing the number of features. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Reduction

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CPSNet: Comprehensive Enhancement Representation for Polyp Segmentation Task

CPSNet: Comprehensive Enhancement Representation for Polyp S...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Cai, Jiati Liu, Xiaogang Yang, Hongjie Ding, Yi Zhong, Ting Qin, Zhen Network and Data Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of China Chengdu China Department of Gastroenterology and Hepatology University of Electronic Science and Technology of China Chengdu China School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9798350368741

Accurately segmenting polyp regions in colonoscopy images is crucial for the diagnosis and intervention of colorectal cancer. However, the task of polyp segmentation remains challenging due to the diverse size and shape variations among polyps, their extreme similarity to the background, and frequent rotation of the lens, which further increases the diversity in polyp presentation. To address these challenges effectively, we propose a comprehensive polyp segmentation network (CPSNet). Specifically, we introduce a Comprehensive Spatial Feature Extraction Module (CFEM) that progressively and densely integrates features while forming receptive windows with various shapes. This enables enhanced perception of polyps at manifold sizes and shapes. Additionally, we propose a Fine-grained Region Strengthen Module (FGSM) to supplement uncertain areas around polyps by mitigating background noise interference. In terms of training strategy, we further introduce a Rotation-augmented Constrained Loss (RC Loss), which reinforces consistency constraints on polyp images under multiple rotation angles. Qualitative and quantitative experiments conducted on five public datasets demonstrate both the plug-and-play capability of CFEM as well as the effectiveness and excellence achieved by CPSNet. © 2025 IEEE.

关键词： colonoscopy computer vision polyp segmentation representation enhancement

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Practical privacy-preserving mixing protocol for Bitcoin 26

Practical privacy-preserving mixing protocol for Bitcoin

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26th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2023

作者： Chang, Qianqian Xu, Lin Zhang, Lei Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai200062 China Science and Technology on Communication Security Laboratory Chengdu610041 China Engineering Research Center of Software/Hardware Co-design Technology and Application Ministry of Education Shanghai200062 China

ISBN: (纸本)9798350331684

The privacy of Cryptocurrencies are of great concern in various fields. Researches has shown that pseudonyms, which are used in Bitcoin, only provide weak privacy. The privacy of users may be put at risk under deanonymization attacks. The exisiting schemes typically require a trusted-third party to achieve anonymity, however this usually faces a single-point fault. In addition, existing schemes suffer from high communication complexity and impracticality. This paper proposes a practical privacy-preserving mixing protocol for Bitcoin to achieve unlink-ability of input and output address of transactions. Compared to existing schemes, our protocol improves practicality. The communication complexity of our protocol is linearly related to the number of peers. Moreover, our protocol is scalable as it works not only for Bitcoin, but also for other cryptocurrencies. © 2023 IEEE.

关键词： Computational complexity

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A Web Service Recommendation Method Based on Adaptive Gate Network and xDeepFM 1

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22nd International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2022

作者： Tao, Zhi Cao, Buqing Ye, Hongfan Kang, Guosheng Peng, Zhenlian Wen, Yiping School of Computer Science and Engineering and Hunan Key Laboratory of Service Computing and New Software Service Technology Hunan University of Science and Technology Hunan Xiangtan China School of Computer and Artificial Intelligence Huaihua University Huaihua China

ISBN: (数字)9783031226779

ISBN: (纸本)9783031226762

With the rapid development of service computing technology, more and more companies and organizations are encapsulating and publishing their operational data or resources to the Internet in the form of Web services, resulting in an exponential increase in the number of Web services. To automatically generate or recommend a group of Web services according to the user's natural language requirements description, to build a Mashup application to meet the user's requirement is a hot topic in service computing. Some researchers enhance the quality of Web service recommendation by using auxiliary information into the recommendation system. However, they mainly focus on adding external information (e.g., pre-training of external corpora) to enhance semantic features, while some internal statistical features of the corpus such as word distribution on labels and frequency are not fully exploited. Compared to other exterior knowledge, statistical features are naturally compatible with Web service recommendation tasks. To fully exploit the statistical features, this paper proposes a Web service recommendation method based on adaptive gate network and xDeepFM model. In this method, firstly, the description document of Web services is taken as the basic corpus, the semantic and statistical information in the corpus are mined by utilizing the adaptive gate network, and the statistical features are encoded by a variational encoder. Secondly, the similarity between Web services is derived from the semantic features, at the same time the popularity and co-occurrence of Web services are calculated. Thirdly, the xDeepFM model is used to mine the explicit and implicit higher-order interactions in the sparse matrix which consists of the above information to recommend Web services for Mashup application. Finally, a multiple sets of experiments based on the dataset crawled from the ProgrammableWeb have been conducted to evaluate the proposed method and the experimental result shows that t

关键词： Web services

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Impact analysis of rocket gas jet on offshore platform 3

Impact analysis of rocket gas jet on offshore platform

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2024 3rd International Conference on Aerospace, Aerodynamics and Mechatronics engineering, AAME 2024

作者： Xu, Jun Gui, Hongbin Zhao, Weidong Gong, Qingtao Zhang, Yan School of Ocean Engineering Harbin Institute of Technology Weihai264209 China State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial Equipment Dalian University of Technology Liaoning Dalian116024 China Ludong University Shandong Maritime and Aerospace Equipment Technology Innovation Center Yantai264025 China

To prevent the high-temperature and high-pressure impact jet from breaking the surface structure of the launching platform during the launch of the rocket at sea, the impact effect of the gas jet of the sea rocket launch on the launch platform deserves to be studied. This paper considers the motion attitude of the launch platform in seawater and the presence of multiple gases in the rocket exhaust jet. Based on the realizable k-ϵ turbulence model, the numerical model of the gas jet impacting on the launch platform from the sea launch is built, and the finite volume method is used to discretize the control equations, aiming to obtain the impact cloud image of the gas jet of the rocket at different launch heights and different launch angles on the launch platform surface and to analyze the change of the impact pressure history. The results show that the initial launch height and launch angle of the rocket have a great influence on the peak impact pressure on the surface of the launch platform. The impact effect of the gas jet is mainly related to the relative position of the launch platform surface in the Mach disk. Reasonable changes in the launching angle can effectively reduce the impact of the gas jet on the launch platform and provide technical references for the launch of the rocket at sea. © Published under licence by IOP Publishing Ltd.

关键词： Exhaust gases

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Intention Estimation of Adversarial Spatial Target Based on Fuzzy Inference

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Intelligent Automation & Soft Computing 2023年第3期35卷 3627-3639页

作者： Wenjia Xiang Xiaoyu Li Zirui He Chenjing Su Wangchi Cheng Chao Lu Shan Yang School of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu610054China Institute of Logistics Science and Technology Beijing100166China Science and Technology on Altitude Simulation Laboratory Sichuan Gas Turbine Establishment Aero Engine Corporation of ChinaMianyang621000China Department of Chemistry Physics and Atmospheric SciencesJackson State UniversityJacksonMS 39217USA

Estimating the intention of space objects plays an important role in air-craft design,aviation safety,military and otherﬁelds,and is an important refer-ence basis for air situation analysis and command *** paper studies an intention estimation method based on fuzzy theory,combining prob-ability to calculate the intention between two *** method takes a space object as the origin of coordinates,observes the target’s distance,speed,relative heading angle,altitude difference,steering trend and etc.,then introduces the spe-ciﬁc calculation methods of these *** calculation,values are input into the fuzzy inference model,andﬁnally the action intention of the target is obtained through the fuzzy rule table and historical weighted ***-iﬁed by simulation experiment,the target intention inferred by this method is roughly the same as the actual behavior of the target,which proves that the meth-od for identifying the target intention is effective.

关键词： Intension estimation motion parameters calculation fuzzy inference fuzzy rule table historical weighted probability

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