检索结果-内蒙古大学图书馆

PCA: Semi-Supervised Segmentation with Patch Confidence Adversarial Training

IEEE Transactions on Network science and engineering 2025年

作者： Xu, Zhenghua Yang, Runhe Xu, Zihang Zhang, Shuo Yang, Yuchen Liu, Weipeng Xu, Weichao Chen, Junyang Lukasiewicz, Thomas Leung, Victor C. M. Hebei University of Technology State Key Laboratory of Reliability and Intelligence of Electrical Equipment School of Health Sciences and Biomedical Engineering Tianjin China The University of Hong Kong Department of Electrical and Electronic Engineering Hong Kong The Johns Hopkins University Department of Applied Mathematics and Statistic Baltimore United States Hebei University of Technology School of Artificial Intelligence Tianjin China Hebei Provincial Hospital of Traditional Chinese Medicine Digestive Disease Center Shijiazhuang China Shenzhen University College of Computer Science and Software Engineering Shenzhen China University of Oxford Department of Computer Science University of Oxford United Kingdom Department of Computer Science United Kingdom Vienna University of Technology institute of Logic and Computation nstitute of Logic and Computation Vienna Austria

Deep-learning-based semi-supervised learning (SSL) methods have achieved a strong performance in medical image segmentation, which can alleviate doctors' expensive annotation by utilizing a large amount of unlabeled data. Unlike most existing semi-supervised learning methods, adversarial training methods distinguish samples from different sources by learning the data distribution of the segmentation map, leading the segmenter to generate more accurate predictions. We argue that the current performance restrictions for such approaches are the problems of feature extraction and learning preferences. In this paper, we propose a new semi-supervised adversarial method called Patch Confidence Adversarial Training (PCA) for medical image segmentation. The PCA method's discriminator penalizes patch-level structures, guiding the generator to optimize different patch areas, by leveraging pixel context, the generator is driven to focus on high-frequency features, making it harder to deceive the discriminator and easy to converge to an ideal state, which more effectively guides the segmenter to generate high-quality pseudo-labels. Furthermore, at the discriminator's input, we supplement image information constraints, making it simpler to fit the expected data distribution. Extensive experiments on the Automated Cardiac Diagnosis Challenge (ACDC) 2017 dataset and the Brain Tumor Segmentation (BraTS) 2019 challenge dataset show that our method outperforms the state-of-the-art semi-supervised methods, which demonstrates its effectiveness for medical image segmentation. © 2025 IEEE. All rights reserved.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Privacy-preserving Adversarial Facial Features

arXiv

引用

arXiv 2023年

作者： Wang, Zhibo Wang, He Jin, Shuaifan Zhang, Wenwen Hu, Jiahui Wang, Yan Sun, Peng Yuan, Wei Liu, Kaixin Ren, Kui School of Cyber Science and Technology Zhejiang University China ZJU-Hangzhou Global Scientific and Technological Innovation Center China Alibaba Group China College of Computer Science and Electronic Engineering Hunan University China School of Cyber Science and Engineering Wuhan University China

Face recognition service providers protect face privacy by extracting compact and discriminative facial features (representations) from images, and storing the facial features for real-time recognition. However, such features can still be exploited to recover the appearance of the original face by building a reconstruction network. Although several privacy-preserving methods have been proposed, the enhancement of face privacy protection is at the expense of accuracy degradation. In this paper, we propose an adversarial features-based face privacy protection (AdvFace) approach to generate privacy-preserving adversarial features, which can disrupt the mapping from adversarial features to facial images to defend against reconstruction attacks. To this end, we design a shadow model which simulates the attackers’ behavior to capture the mapping function from facial features to images and generate adversarial latent noise to disrupt the mapping. The adversarial features rather than the original features are stored in the server’s database to prevent leaked features from exposing facial information. Moreover, the AdvFace requires no changes to the face recognition network and can be implemented as a privacy-enhancing plugin in deployed face recognition systems. Extensive experimental results demonstrate that AdvFace outperforms the state-of-the-art face privacy-preserving methods in defending against reconstruction attacks while maintaining face recognition accuracy. Copyright © 2023, The Authors. All rights reserved.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

Verify All Traffic: Towards Zero-Trust In-Network Intrusion Detection against Multipath Routing

引用

IEEE Journal on Selected Areas in Communications 2025年第6期43卷 2155-2171页

作者： Zhao, Ziming Li, Zhaoxuan Xie, Xiaofei Liu, Zhipeng Li, Tingting Yu, Jiongchi Zhang, Fan Chen, Binbin School of Software Technology Zhejiang University Ningbo315100 China College of Computer Science and Technology Zhejiang University Hangzhou310027 China ZJU-Hangzhou Global Scientific and Technological Innovation Center 311200 China Key Laboratory of Blockchain and Cyberspace Governance of Zhejiang Province 310027 China Jiaxing Research Institute Zhejiang University 314000 China Zhengzhou Xinda Institute of Advanced Technology Zhengzhou450001 China Singapore State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China School of Cyber Security UCAS Beijing100049 China School of Computing and Information Systems Singapore Management University Singapore188065 Singapore Advanced Digital Sciences Center Singapore138632 Singapore Singapore University of Technology and Design SingaporeB96049 Singapore

With the popularity of encryption protocols, machine learning (ML)-based traffic analysis technologies have attracted widespread attention. To adapt to modern high-speed bandwidth, recent research is dedicated to advancing zero-trust intrusion detection by offloading feature extraction and model inference into the network dataplane. Especially, with the rise of programmable switches, achieving line-speed ML inference becomes promising. However, existing research only considers a single switch node as a relay to conduct evaluation. This is far from real-world deployments involving multiple switches (given that zero-trust security assumes that threats can originate from anywhere, including within the network), particularly the multi-path routing phenomenon that exists in practice. In this paper, we reveal practical challenges in the context of enabling line-speed model inference in the network dataplane. Furthermore, we propose FCPlane, the forwarding and computing integrated dataplane for zero-trust intrusion detection that aims to enable efficient load balancing while providing reliable traffic analysis results, even against multipath routing. The core idea is to reconcile forwarding and computation to the flowlet level, for which a tailor-made Markov chain model is designed. Based on two public traffic datasets, we evaluate seven state-of-the-art in-network traffic analysis models deployed in four types of topologies (three with multipath routing and one without) to explore performance impact and demonstrate the effectiveness of our proposal. © 1983-2012 IEEE.

关键词： Network intrusion

来源：评论

学校读者我要写书评

暂无评论

A biosensing system employing nanowell microelectrode arrays to record the intracellular potential of a single cardiomyocyte

引用

Microsystems & Nanoengineering 2022年第3期8卷 185-198页

作者： Yuting Xiang Haitao Liu Wenjian Yang Zhongyuan xu Yue Wu Zhajian Tang Zhjing Zhu Zhiyong Zeng Depeng Wang Tianxing Wang Ning Hu Diming Zhang Department of Obstetrics and Gynecology Affiliated Dongguan People's HospitalSouthern Medical UniversityDongguan 523058China Research Center for Inelligent Sensing Systems Zhejiang LaboratoryHangzhou 311100China Research Center for Humanoid Sensing Zhejiang LaboratoryHangzhou 311100China Key Laboratory of Novel Target and Drug Study for Neural Repair of Zhejiang Province School of MedicineSchool of Computer&Computing ScienceZhejiang University City CollegeHangzhou 310015China School of Brain Science and Brain Medicine Zhejiang UniversityHangzhou 310058China School of Automation Nanjing University of Science and TechnologyNanjing 210094China College of Energy and Power Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China E-Link Care Meditech Co. LtdHangzhou 310011China ZJU-Hangzhou Global Scientific and Technological Innovation Center Department of ChemitryZhejiang UniversityHangzhou 310058China

Electrophysiological recording is a widely used method to investigate cardiovascular pathology,pharmacology and developmental *** arrays record the electrical potential of cells in a minimally invasive and highthroughput ***,commonly used microelectrode arays primarily employ planar microelectrodes and cannot work in applications that require a recording of the intracellular action potential of a single *** this study,we proposed a novel measuring method that is able to record the intracellular action potential of a single cardiomyocyte by using a nanowell patterned microelectrode array(NWMEA).The NWMEA consists of five nanoscale wells at the center of each circular planar *** pulse electroporation was applied to the NWMEA to penetrate the cardiomyocyte membrane,and the intracellular action potential was continuously *** intracellular potential recording of cardiomyocytes by the NWMEA measured a potential signal with a higher quality(213.76±25.85%),reduced noise root-mean-square(~33%),and higher signal-to-noise ratio(254.36±12.61%)when compared to those of the extracellular *** to previously reported nanopillar microelectrodes,the NWMEA could ensure single cell electroporation and acquire high-quality action potential of cardiomyocytes with reduced fabrication *** NWMEA-based biosensing system is a promising tool to record the intracellular action potential of a single cell to broaden the usage of microelectrode arrays in electrophysiological investigation.

关键词： arrays potential record

来源：评论

学校读者我要写书评

暂无评论

Shared-Space Autoencoders with Randomized Skip Connections for Building Footprint Detection with Missing Views 25th

Shared-Space Autoencoders with Randomized Skip Connections f...

引用

25th International Conference on Pattern Recognition Workshops, ICPR 2020

作者： Ashiotis, Giannis Oldfield, James Chrysostomou, Charalambos Christoudias, Theodoros Nicolaou, Mihalis A. Computation-Based Science and Technology Research Center The Cyprus Institute Lefkosia Cyprus Climate and Atmosphere Research Center The Cyprus Institute Lefkosia Cyprus School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom

ISBN: (纸本)9783030687861

Recently, a vast amount of satellite data has become available, going beyond standard optical (EO) data to other forms such as synthetic aperture radars (SAR). While more robust, SAR data are often more difficult to interpret, can be of lower resolution, and require intense pre-processing compared to EO data. On the other hand, while more interpretable, EO data often fail under unfavourable lighting, weather, or cloud-cover conditions. To leverage the advantages of both domains, we present a novel autoencoder-based architecture that is able to both (i) fuse multi-spectral optical and radar data in a common shared-space, and (ii) perform image segmentation for building footprint detection under the assumption that one of the data modalities is missing–resembling a situation often encountered under real-world settings. To do so, a novel randomized skip-connection architecture that utilizes autoencoder weight-sharing is designed. We compare the proposed method to baseline approaches relying on network fine-tuning, and established architectures such as UNet. Qualitative and quantitative results show the merits of the proposed method, that outperforms all compared techniques for the task-at-hand. © 2021, Springer Nature Switzerland AG.

关键词： Synthetic aperture radar

来源：评论

学校读者我要写书评

暂无评论

Adaptive Fuzzy Weighted Broad Network for Imbalanced Medical Diagnosis

Adaptive Fuzzy Weighted Broad Network for Imbalanced Medical...

引用

Medical Artificial Intelligence (MedAI), IEEE International Conference on

作者： Leqi Tang Wuxing Chen Zhiwen Yu Huan Wang Jianming Lv Kaixiang Yang South China University of Technology School of Future Technology Guangzhou China South China University of Technology School of Computer Science and Engineering Guangzhou China Guangdong Institute of Scientific & Technical Information Industrial Technology Research Center Guangzhou China

ISBN: (数字)9798350377613

ISBN: (纸本)9798350377620

Medical diagnosis is crucial for providing quality healthcare. Machine learning techniques have received much attention in the medical field for their ability to provide efficient handling of diverse diagnostic problems. Nonetheless, machine learning often faces performance degradation due to imbalanced data in medical diagnosis, and also requires models that can quickly diagnose problems to facilitate doctors' medical decisions. To address this problem, we introduce Adaptive Fuzzy Weighted Broad Learning System (AFWBLS), which aims to use a variety of technologies to improve medical diagnostic accuracy. The adaptive weight enables BLS to take Intra-class density, inter-class density, the distribution of classes and frontier into consideration, which can reduce the impact of imbalanced data. The fuzzy weight gives BLS the ability to reduce the impact of noise and outliers. The Experiment shows that AFWBLS has good performance on imbalanced medical datasets and AFWBLS can maintain stable in datasets with large imbalanced rates.

关键词： Learning systems Degradation Adaptive systems Noise Machine learning Learning (artificial intelligence) Data models Medical diagnosis Medical diagnostic imaging Faces

来源：评论

学校读者我要写书评

暂无评论

A Comparative Study of the Coulomb’s and Franklin’s Laws Inspired Algorithm (CFA) with Modern Evolutionary Algorithms for Numerical Optimization 1st

A Comparative Study of the Coulomb’s and Franklin’s Laws I...

引用

1st International Conference on Pervasive Knowledge and Collective Intelligence on Web and Social Media, PerSOM 2022

作者： Ghasemi, Mojtaba Zare, Mohsen Zahedi, Amir Hemmati, Rasul Abualigah, Laith Forestiero, Agostino Department of Electronics and Electrical Engineering Shiraz University of Technology Shiraz Iran Department of Electrical Engineering Faculty of Engineering Jahrom University Fras Jahrom Iran Department of Electrical and Computer Engineering Tarbiat Modares University Tehran Iran Department of Electrical and Computer Engineering Marquette University MilwaukeeWI United States Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman Jordan Faculty of Information Technology Middle East University Amman11831 Jordan Applied Science Research Center Applied Science Private University Amman11931 Jordan School of Computer Sciences Universiti Sains Malaysia Pulau Pinang George Town11800 Malaysia Computer Science Department Prince Hussein Bin Abdullah Faculty for Information Technology Al Al-Bayt University Mafraq25113 Jordan Institute for High Performance Computing and Networking National Research Council of Italy Rende Italy

ISBN: (纸本)9783031314681

Coulomb and Franklin’s electricity laws are used in this paper to model an efficient optimization algorithm based on electric particle searches, which has been named CFA. For the CFA optimizer, the influence of electrically charged particles on each other in charged things has been predicated on the forces of attraction and repulsion. Evolutionary algorithms (EA) such as hybrid real coded genetic algorithm (RCGA) which combines the global and local search (GL-25), differential evolution (DE) with strategy adaptation (SaDE), composite DE (CoDE), the improved standard particle swarm optimization 2011 (SPSO2013) and the grouped comprehensive learning PSO (GCLPSO) are compared to the CFA optimizer for finding global solutions of seven basic benchmark functions of high dimension D = 50. (GCLPSO). Experiments have shown that the suggested CFA optimizer is quite effective and competitive for the benchmark functions. Note that the source code of the CFA algorithm is publicly available at https://***/projects/cfa, https://***/matlabcentral/fileexchange/127727-franklin-s-laws-inspired-algorithm-cfa. © 2023, ICST Institute for computer sciences, Social Informatics and Telecommunications engineering.

关键词： Charged particles

来源：评论

学校读者我要写书评

暂无评论

Domain watermark: effective and harmless dataset copyright protection is closed at hand 23

Domain watermark: effective and harmless dataset copyright p...

引用

Proceedings of the 37th International Conference on Neural Information Processing Systems

作者： Junfeng Guo Yiming Li Lixu Wang Shu-Tao Xia Heng Huang Cong Liu Bo Li Department of Computer Science University of Maryland ZJU-Hangzhou Global Scientific and Technological Innovation Center and School of Cyber Science and Technology Zhejiang University Department of Computer Science Northwestern University Tsinghua Shenzhen International Graduate School Tsinghua University Department of Electronic and Computer Engineering UC Riverside Department of Computer Science University of Illinois Urbana-Champaign and Department of Computer Science University of Chicago

The prosperity of deep neural networks (DNNs) is largely benefited from open-source datasets, based on which users can evaluate and improve their methods. In this paper, we revisit backdoor-based dataset ownership verification (DOV), which is currently the only feasible approach to protect the copyright of open-source datasets. We reveal that these methods are fundamentally harmful given that they could introduce malicious misclassification behaviors to watermarked DNNs by the adversaries. In this paper, we design DOV from another perspective by making watermarked models (trained on the protected dataset) correctly classify some 'hard' samples that will be misclassified by the benign model. Our method is inspired by the generalization property of DNNs, where we find a hardly-generalized domain for the original dataset (as its domain watermark). It can be easily learned with the protected dataset containing modified samples. Specifically, we formulate the domain generation as a bi-level optimization and propose to optimize a set of visually-indistinguishable clean-label modified data with similar effects to domain-watermarked samples from the hardly-generalized domain to ensure watermark stealthiness. We also design a hypothesis-test-guided ownership verification via our domain watermark and provide the theoretical analyses of our method. Extensive experiments on three benchmark datasets are conducted, which verify the effectiveness of our method and its resistance to potential adaptive methods. The code for reproducing main experiments is available at https://***/JunfengGo/Domain-Watermark.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Multilayer broadband switchable absorbers based on phase-change materials

Multilayer broadband switchable absorbers based on phase-cha...

引用

2023 Active Photonic Platforms, APP 2023

作者： Emrose, Md Tanvir Payne, Emily L. You, Chenglong Veronis, Georgios School of Electrical Engineering and Computer Science Louisiana State University Baton RougeLA70803 United States Center for Computation and Technology Louisiana State University Baton RougeLA70803 United States Department of Physics Brigham Young University - Idaho RexburgID83460 United States Department of Physics and Astronomy Louisiana State University Baton RougeLA70803 United States

ISBN: (纸本)9781510665088

We introduce multilayer structures with the phase-change material germanium-antimony-tellurium (GST) for use as broadband switchable absorbers in the infrared wavelength range. We use a memetic optimization algorithm coupled with the transfer-matrix method to optimize both the material composition and the layer thicknesses of the multilayer structures. We show that in the optimized structures near perfect absorption can be switched to very low absorption in a broad wavelength range by switching GST from its crystalline to its amorphous phase. Our results could pave the way to a new class of broadband switchable absorbers and thermal sources in the infrared wavelength range. © 2023 SPIE.

关键词： Phase change materials

来源：评论

学校读者我要写书评

暂无评论

IoT Security Frameworks: A Comparative Review with a Focus on Privacy 2

IoT Security Frameworks: A Comparative Review with a Focus o...

引用

2nd International Conference on Cyber Resilience, ICCR 2024

作者： Al-Hasnawi, Abduljaleel Niu, Yitong Tawfeq, Jamal F. Ranjan Pradhan, Manas Salahat, Mohammed Ghazal, Taher M. Ministry Of Higher Education And Scientific Research Baghdad Iraq College Of Information Technology Imam Ja'afar Al-Sadiq University Department Of Communication Technology Engineering Baghdad Iraq School Of Aeronautical Engineering AnYang University Anyang China Medical Technical College Al-Farahidi University Department Of Medical Instrumentation Technical Engineering Baghdad10070 Iraq School Of Computing Skyline University College University City Sharjah Sharjah United Arab Emirates College Of Engineering And Technology University Of Science And Technology Of Fujairah Fujairah United Arab Emirates Khalifa University Centre For Cyber Physical Systems Computer Science Department United Arab Emirates Center For Cyber Security Faculty Of Information Science And Technology Selangor Bangi43600 Malaysia

ISBN: (纸本)9798350394962

The privacy of sensitive data within the Internet of Things (IoT) is at risk due to potential privacy violations. These violations can occur through illegal access by external entities, as well as inadvertent disclosures or intentional attacks by those within the system who exceed their authorized access privileges. Furthermore, there needs to be more control experienced by data owners regarding their sensitive data as it transitions from their domain to other entities within the Internet of Things (IoT) ecosystem. Numerous methods have been presented in the academic literature over the past few years to effectively tackle the privacy concerns associated with the Internet of Things (IoT). This paper aims to classify existing literature by organizing it according to the specific technology or technique employed to safeguard privacy. The classification encompasses four primary areas of privacy solutions, specifically, solutions based on encryption, solutions based on identity management, solutions based on policy enforcement, and solutions focused on self-protection. The paper examines various state-of-the-art solutions within each category. It begins by providing a broad comparison between these solutions and our work. Subsequently, it focuses on a specific comparison of the privacy objectives of the offered PEFM solutions. © 2024 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：