检索结果-内蒙古大学图书馆

Deep Learning and Federated Learning in Breast Cancer Screening and Diagnosis: A Systematic Review

IEEE Access 2025年 13卷 76322-76351页

作者： Ciobotaru, Alexandru Corches, Cosmina Gota, Dan Miclea, Liviu Technical University of Cluj-Napoca Faculty of Automation and Computer Science Automation Department Cluj-Napoca400114 Romania

Breast cancer remains one of the leading causes of death among women worldwide. Early detection and diagnosis are crucial for effective treatment and improved patient outcome. In recent years, both deep learning and federated learning have demonstrated significant advancements in terms of their ability to reliably and securely diagnose breast cancer using various imaging techniques. Consequently, a thorough summary of recent advancements in the field of breast cancer screening and diagnosis using deep learning and federated learning, along with future research directions, is imperative. This study presents a comprehensive review of recent deep learning and federated learning-based methods for breast cancer screening and diagnosis from the classification, segmentation, and detection viewpoints using ultrasonography, mammography, magnetic resonance imaging, and histopathology images. In addition, novel deep learning and federated learning architectures that are used to reliably and securely diagnose breast cancer using various imaging techniques are highlighted. Finally, a discussion of the associated challenges and future research directions are presented. © 2013 IEEE.

关键词： Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Multifrequency measurement system with no frequency ambiguity based on two frequency-space mappings

引用

Optical Engineering 2025年第3期64卷

作者： Zhang, Jiahong Ma, Di Li, Peiqi Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming China Kunming University of Science and Technology Yunnan Key Laboratory of Computer Technology Applications Kunming China

Multifrequency measurement system with no frequency ambiguity based on two frequency-space mappings has been designed and investigated. By simultaneously mapping the unknown frequencies with a certain frequency shift onto non-flat optical frequency combs (OFCs) and obtaining two beat frequency signals using two balanced photodetectors (BPD), the channel where the measured signal is located can be determined, achieving instantaneous measurement of multifrequencies while effectively addressing five possible types of frequency ambiguity. Simulation results indicate that when the comb line spacing of the OFC is designed as 2 GHz, the measurement range of the system is 0.1 to 30 GHz, with a measurement error within ±1 MHz and a measurement resolution of 2.7 MHz. Furthermore, by adjusting the comb line spacing of the OFC to 4 GHz, the frequency measurement range can be extended to 60 GHz. © 2025 Society of Photo-Optical Instrumentation Engineers (SPIE)

关键词： Electric frequency measurement

来源：评论

学校读者我要写书评

暂无评论

Machine Learning-Based Methods for Materials Inverse Design: A Review

引用

computers, Materials & Continua 2025年第2期82卷 1463-1492页

作者： Yingli Liu Yuting Cui Haihe Zhou Sheng Lei Haibin Yuan Tao Shen Jiancheng Yin Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming650093China Yunnan Key Laboratory of Computer Technologies Application Kunming University of Science and TechnologyKunming650500China Yunnan Tin Company Limited Tin Industry Branch Gejiu661000China Faculty of Materials Science and Engineering Kunming University of Science and TechnologyKunming650093China

Finding materials with specific properties is a hot topic in materials *** materials design relies on empirical and trial-and-error methods,requiring extensive experiments and time,resulting in high *** the development of physics,statistics,computer science,and other fields,machine learning offers opportunities for systematically discovering new *** through machine learning-based inverse design,machine learning algorithms analyze the mapping relationships between materials and their properties to find materials with desired *** paper first outlines the basic concepts of materials inverse design and the challenges faced by machine learning-based approaches to materials inverse ***,three main inverse design methods—exploration-based,model-based,and optimization-based—are analyzed in the context of different application ***,the applications of inverse design methods in alloys,optical materials,and acoustic materials are elaborated on,and the prospects for materials inverse design are *** authors hope to accelerate the discovery of new materials and provide new possibilities for advancing materials science and innovative design methods.

关键词： Materials inverse design machine learning target properties deep learning new materials discovery

来源：评论

学校读者我要写书评

暂无评论

Multi-Expert Adaptive Selection: Task-Balancing for All-in-One Image Restoration

引用

IEEE Transactions on Circuits and Systems for Video Technology 2025年第5期35卷 4619-4634页

作者： Yu, Xiaoyan Zhou, Shen Li, Huafeng Zhu, Liehuang Beijing Institute of Technology School of Computer Science and Technology Beijing100081 China Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming650500 China Beijing Institute of Technology School of Cyberspace Science and Technology Beijing100081 China

The use of a single image restoration framework to achieve multi-task image restoration has garnered significant attention from researchers. However, several practical challenges remain, including meeting the specific and simultaneous demands of different tasks, balancing relationships between tasks, and effectively utilizing task correlations in model design. To address these challenges, this paper explores a multi-expert adaptive selection mechanism. We begin by designing a feature representation method that accounts for both the pixel channel level and the global level, encompassing low-frequency and high-frequency components of the image. Based on this method, we construct a multi-expert selection and ensemble scheme. This scheme adaptively selects the most suitable expert from the expert library according to the content of the input image and the prompts of the current task. It not only meets the individualized needs of different tasks but also achieves balance and optimization across tasks. By sharing experts, our design promotes interconnections between different tasks, thereby enhancing overall performance and resource utilization. Additionally, the multi-expert mechanism effectively eliminates irrelevant experts, reducing interference from them and further improving the effectiveness and accuracy of image restoration. Experimental results demonstrate that our proposed method is both effective and superior to existing approaches, highlighting its potential for practical applications in multi-task image restoration. © 1991-2012 IEEE.

关键词： Restoration

来源：评论

学校读者我要写书评

暂无评论

Auto-3D-house Design from Structured User Requirements

引用

Machine Intelligence Research 2025年第2期22卷 368-385页

作者： Minkui Tan Qi Chen Zixiong Huang Qi Wu Yuanqing Li Jiaqiu Zhou School of Software Engineering South China University of TechnologyGuangzhou 510006China Faculty of Engineering Computer and Mathematical ScienceUniversity of AdelaideAdelaide SA 5005Australia School of Automation Science and Engineering South China University of TechnologyGuangzhou 510006China

We study the task of automated house design,which aims to automatically generate 3D houses from user ***,in the automatic system,it is non-trivial due to the intrinsic complexity of house designing:1)the understanding of user requirements,where the users can hardly provide high-quality requirements without any professional knowledge;2)the design of house plan,which mainly focuses on how to capture the effective information from user *** address the above issues,we propose an automatic house design framework,called auto-3D-house design(A3HD).Unlike the previous works that consider the user requirements in an unstructured way(e.g.,natural language),we carefully design a structured list that divides the requirements into three parts(i.e.,layout,outline,and style),which focus on the attributes of rooms,the outline of the building,and the style of decoration,*** the processing of architects,we construct a bubble diagram(i.e.,graph)that covers the rooms′attributes and relations under the constraint of *** addition,we take each outline as a combination of points and orders,ensuring that it can represent the outlines with arbitrary ***,we propose a graph feature generation module(GFGM)to capture layout features from the bubble diagrams and an outline feature generation module(OFGM)for outline ***,we render 3D houses according to the given style requirements in a rule-based *** on two benchmark datasets(i.e.,RPLAN and T3HM)demonstrate the effectiveness of our A3HD in terms of both quantitative and qualitative evaluation metrics.

关键词： Automated house design user requirements understanding outline processing layout generation graph feature generation.

来源：评论

学校读者我要写书评

暂无评论

Transmission scheme based on collaborative AUV communication 16

Transmission scheme based on collaborative AUV communication

引用

16th International Conference on Signal Processing Systems, ICSPS 2024

作者： Sun, Jiahao Qi, Chao Liu, Zengli Zhao, Xuanzhi Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Computer Center Kunming University of Science and Technology Kunming China

ISBN: (纸本)9781510689251

Underwater wireless sensor networks can monitor ocean information, which provides a new approach to marine environmental monitoring, disaster warning and resource exploration. However, the development of underwater wireless sensing networks is limited by factors such as ocean currents and limited energy of the sensors themselves. Based on this situation, this paper proposes a transmission scheme based on collaborative communication with autonomous underwater vehicles (AUVs), in which autonomous underwater vehicles (AUVs) are used as a tool for distributed data collection and forwarding, which can solve the problem of imbalanced energy consumption of sensor nodes in the traditional multi-hop underwater communication network. At the same time, we consider the influence of ocean currents on the node positions to maximize the imitation of the real underwater environment, and the simulation results show that the proposed transmission scheme for collaborative communication with AUVs can significantly prolong the service life of underwater sensor networks. © 2025 SPIE.

关键词： Autonomous underwater vehicles

来源：评论

学校读者我要写书评

暂无评论

Learning Video Salient Object Detection Progressively From Unlabeled Videos

引用

IEEE Transactions on Multimedia 2025年 27卷 2423-2435页

作者： Xu, Binwei Jiang, Qiuping Liang, Haoran Zhang, Dingwen Liang, Ronghua Chen, Peng Ningbo University Faculty of Information Science and Engineering Ningbo315211 China Zhejiang University of Technology College of Computer Science and Technology Hangzhou310023 China Northwestern Polytechnical University Brain and Artificial Intelligence Laboratory School of Automation Xi'an710072 China

Recently, deep learning-based video salient object detection (VSOD) has achieved some breakthroughs, but these methods rely on expensive annotated videos with pixel-wise annotations or weak annotations. In this paper, based on the similarities and differences between VSOD and image salient object detection (SOD), we propose a novel VSOD method via a progressive framework that locates and segments salient objects in sequence without utilizing any video annotation. To efficiently use the knowledge learned in the SOD dataset for VSOD efficiently, we introduce dynamic saliency to compensate for the lack of motion information of SOD during the locating process while maintaining the same fine segmenting process. Specifically, we utilize the coarse locating model trained on the image dataset, to identify frames with both static and dynamic saliency. Locating results of these frames are selected as spatiotemporal location labels. Moreover, by tracking salient objects in adjacent frames, the number of spatiotemporal location labels is increased. On the basis of these location labels, a two-stream locating network with an optical flow branch is proposed to capture salient objects in videos. The results with respect to five public benchmarks demonstrate that our method outperforms the state-of-the-art weakly and unsupervised methods. © 1999-2012 IEEE.

关键词： Self-supervised learning

来源：评论

学校读者我要写书评

暂无评论

Privacy preserving federated learning with convolutional variational bottlenecks

引用

Cybersecurity 2025年第1期8卷 1-22页

作者： Scheliga, Daniel Mäder, Patrick Seeland, Marco Department of Computer Science and Automation Technische Universität Ilmenau Helmholtzplatz 5 Thuringia Ilmenau 98693 Germany Faculty of Biological Sciences Friedrich Schiller University Jena Germany

Gradient Inversion (GI) attacks are a ubiquitous threat in Federated Learning as they exploit gradient leakage to reconstruct supposedly private training data. Recent work has proposed to prevent gradient leakage without loss of model utility by incorporating a PRivacy EnhanCing mODulE (PRECODE) based on variational modeling. Without further analysis, it was shown that PRECODE successfully protects against GI attacks. In this paper, we make multiple contributions. First, we investigate the effect of PRECODE on GI attacks to reveal its underlying working principle. We show that variational modeling introduces stochasticity into the gradients of PRECODE and the subsequent layers in a neural network. The stochastic gradients of these layers prevent iterative GI attacks from converging. Second, we formulate an attack that disables the privacy preserving effect of PRECODE by purposefully omitting stochastic gradients during attack optimization. To preserve the privacy preserving effect of PRECODE, our analysis reveals that variational modeling must be placed early in the network. However, early placement of PRECODE is typically not feasible due to reduced model utility and the exploding number of additional model parameters. Therefore, as a third contribution, we propose a novel privacy module—the Convolutional Variational Bottleneck (CVB)—that can be placed early in a neural network without suffering from these drawbacks. We conduct an extensive empirical study on three seminal model architectures and six image classification datasets. We find that all architectures are susceptible to GI attacks, which can be prevented by our proposed CVB. Compared to PRECODE, we show that our novel privacy module requires fewer trainable parameters, and thus computational and communication costs, to effectively preserve privacy. © The Author(s) 2025.

关键词： Data privacy Deep Learning Federated Learning Gradient Inversion attack Gradient leakage

来源：评论

学校读者我要写书评

暂无评论

Measuring Fairness in AI Explanations with LEADR: Local Explanation Amplification Disparity Ratio 22nd

Measuring Fairness in AI Explanations with LEADR: Local Ex...

引用

22nd International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2024

作者： Shoeibi, Niloufar DeGange, Jonathan Shoeibi, Nastaran Shoeibi, Ali Department of Computer Science and Automation Faculty of Sciences Universidad de Salamanca Salamanca Spain LLP Madrid Spain LLP Washington United States Mazandaran University of Science and Technology Babol Iran

ISBN: (纸本)9783031704147

We investigate the fairness of local explanations in AI models by comparing the mean explanations for privileged and unprivileged groups across various datasets and model types. Specifically, we train linear, multi-layer perceptron, and explainable boosting machine (EBM) models, on several key academic datasets. Local explanations are generated using both post-hoc methods (LIME), and direct methods - logistic regression, integrated gradients and EBM local feature importance. By comparing these explanations across models and methods, we introduce a new metric, the Local Explanation Amplification Disparity Ratio (LEADR), to measure disparities in feature attribution between privileged and unprivileged groups. Our preliminary findings suggest that transparent Whitebox models may exhibit a tendency to display greater disparity in bias than opaque Blackbox models. This insight encourages further research into bias mitigation strategies that are tailored to different algorithm types, with the goal of minimizing undesired bias in AI systems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Logistic regression

来源：评论

学校读者我要写书评

暂无评论

Reverse-Engineering Optimization Techniques of High-Level Synthesis: Practical Insights into Accelerating Applications with AMD-Xilinx Vitis

引用

IEEE Transactions on computer-Aided Design of Integrated Circuits and Systems 2025年

作者： Koronis, Jorge Garnica, Oscar Hidalgo, J. Ignacio Davila, Juan Lanchares Spain Department of Computer Architecture and Automation Faculty of Computer Science Universidad Complutense de Madrid Spain

Modern AI applications contain computationally expensive sections. Accelerator cards and tools like AMD Vitis HLS leverage high-level synthesis and hardware (HW) optimizations to create custom HW designs to accelerate ***, the learning curve is steep, even for those with previous knowledge of HW design, due to the complexity of the optimization techniques and limited information on their interactions and HW effects. This paper quantitatively analyzes the interactions of optimization techniques after reverse engineering Vitis' optimization directives, both in isolation and in *** 150 experiments were conducted to investigate three distinct goals: assessing pragma behavior and the rules governing pragma application and optimizations, modeling Vitis HLS latency estimates, and evaluating the impact of optimizations on design space exploration, specifically area and latency. These experiments involve different combinations and placements of optimizations in the loop and function hierarchy of the test bench. Our findings offer guidance on using Vitis pragmas and identify promising configurations for optimizing latency and area. © 1982-2012 IEEE.

关键词： Reverse engineering

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：