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2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)最新文献

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Pixel-Level Feature Clustering Learning for Image Anomaly Detection and Localization 图像异常检测与定位的像素级特征聚类学习
Huang Chao
Image anomaly detection and localization not only need to provide image-level anomaly judgment but also need to locate pixel-level anomaly areas. This paper proposes a model named pixelAD, which builds an end-to-end network through pixel- level feature clustering learning to solve this problem. The normal prototype is obtained during training by clustering the normal pixel-level features. We generate pixel-level cluster labels of normal samples according to the prototypes, which guide the model to update parameters by calculating the assignment loss. For inference, pixelAD directly outputs the pixel-level anomaly score end-to-end. The experimental results of the real industrial dataset MVTecAD show that PixelAD has an excellent performance in anomaly detection and anomaly localization.
图像异常检测与定位不仅需要提供图像级的异常判断,还需要定位像素级的异常区域。本文提出了一个名为pixelAD的模型,该模型通过像素级特征聚类学习构建端到端网络来解决这一问题。在训练过程中,通过对正常像素级特征聚类得到正常原型。我们根据原型生成正常样本的像素级聚类标签,通过计算分配损失来指导模型更新参数。对于推理,pixelAD直接端到端输出像素级异常评分。在真实工业数据集MVTecAD上的实验结果表明,PixelAD在异常检测和异常定位方面具有优异的性能。
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引用次数: 0
Joint Positioning of Two Nodes via Direction Finding of Signals of Opportunity and Cooperative Range Measurement 基于机会信号测向和协同测距的两节点联合定位
Junlin Li, R. Chen, Xiangyu Peng, Wenrong Chen, Xinyu Hu, Q. Wan
In the study of radiation source positioning, there are some positioning errors about the target node based on the Angle of arrival (AOA) measurement method. On this basis, how to effectively use the information between nodes to improve positioning accuracy has been a research hotspot. This paper uses two nodes as an example. Using the range information between two nodes to conduct a one-dimensional angle search can determine the position coordinates of two nodes on the plane. Aim to improve the Direction Finding (DF) and positioning accuracy of a single node by using the distance between two adjacent nodes. The experimental results show that the proposed positioning method effectively improves the positioning accuracy of a single node.
在辐射源定位研究中,基于到达角(AOA)测量方法的目标节点定位存在一定误差。在此基础上,如何有效利用节点间信息提高定位精度成为研究热点。本文以两个节点为例。利用两个节点之间的距离信息进行一维角度搜索,可以确定两个节点在平面上的位置坐标。目的利用相邻两个节点之间的距离提高单个节点的测向和定位精度。实验结果表明,所提出的定位方法有效地提高了单个节点的定位精度。
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引用次数: 0
A Polarization-Independent Transmissive Metalens In The Microwave Band 微波波段中与偏振无关的透射超透镜
Wang Ling, Yang Xishu, G. Feng, Teng Shuhua, Tan Zhiguo, Zhang Xing, Lou Jun
The metalens plays an irreplaceable role in scientific technologies for its gain enhancement and focusing characteristics. However, there are few studies on polarization-independent metalens in the microwave band. In this paper, a polarization-independent transmissive metalens working in the 20 GHz is proposed and designed. Simulation results verify that the metalens can focus the incident wave with an arbitrary polarization state in the working frequency. The designed metalens has potential applications in high-gain antennas and microwave imaging.
超构透镜以其增益增强和聚焦特性在科学技术中具有不可替代的作用。然而,微波波段中与极化无关的超构透镜的研究很少。提出并设计了一种工作在20 GHz频段的非偏振透射超构透镜。仿真结果表明,该超透镜能够在工作频率范围内聚焦任意偏振态的入射波。所设计的超构透镜在高增益天线和微波成像方面具有潜在的应用前景。
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引用次数: 0
Research on Security Technology of Sensing Terminal of Internet of Things 物联网传感终端安全技术研究
Li Xianli, Pan Wei, Wang Yisheng, Li Ming, Liu Guosong
The Internet of Things is widely used in industry, agriculture, health, urban management and other fields, the sensing terminal is an important part of IoT system, the security of sensing terminal directly affects the whole security of IoT system. This paper proposes the corresponding security measures of the sensing terminal of IoT system, such as physical security, access security, communication security, equipment security, data security, furthermore, we have verified it with experiments. It is of great significance for the selection, deployment, operation and maintenance the sensing terminal of IoT system, and has important application value for designing and producing the sensing terminal of IoT system.
物联网广泛应用于工业、农业、卫生、城市管理等领域,传感终端是物联网系统的重要组成部分,传感终端的安全与否直接影响到整个物联网系统的安全。本文提出了物联网系统传感终端的物理安全、接入安全、通信安全、设备安全、数据安全等相应的安全措施,并通过实验进行了验证。对物联网系统传感终端的选择、部署、运维具有重要意义,对物联网系统传感终端的设计和生产具有重要的应用价值。
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引用次数: 1
A Chaos-Based and Ensembled Method for Outlier Detection 一种基于混沌集成的离群点检测方法
Li Wei
With the advent of the Big Data era, anomaly detection has become an important tool for screening the validity of data. Many well-established distance-based or correlation-based anomaly detection methods are widely used for various structured and feature-based datasets with the increasing size of data. However, different method strategies have different focuses, leading to large deviations in anomaly detection results for the same dataset using different methods, which poses a great challenge to anomaly detection research. In this paper, a new strategy is proposed for anomaly detection using integrated methods. By using a two-stage process of the sliding window aggregation method, the strategy uses a multi-model anomaly scoring method and a uniform quantitative criterion filtering to obtain a suitable anomaly scoring.
随着大数据时代的到来,异常检测已经成为筛选数据有效性的重要工具。随着数据量的不断增加,许多基于距离或相关性的成熟异常检测方法被广泛应用于各种结构化和基于特征的数据集。然而,不同的方法策略有不同的侧重点,导致使用不同的方法对同一数据集的异常检测结果存在较大的偏差,这给异常检测研究带来了很大的挑战。本文提出了一种综合方法进行异常检测的新策略。该策略采用滑动窗口聚合法的两阶段过程,采用多模型异常评分方法和统一的定量准则过滤,获得合适的异常评分。
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引用次数: 0
Deep Learning Techniques for Breast Cancer Mitotic Cell Detection 乳腺癌有丝分裂细胞检测的深度学习技术
Jiquan Li, Laixiang Qiu, Yujun Yang, Wang Zhou
Breast cancer is one of the highest incidence in women's cancer, The pathological diagnosis of breast cancer can be used to evaluate the invasion of tumors and provide important information for accurate diagnosis and treatment. Statistics the number of mitosis cells in breast cancer is one of the important indicators of breast cancer division. In this paper, we summarized the current mainstream methods of mitosis cells detection. These methods are mainly implemented based on deep learning, and discussing the results of some of the methods, comparison and evaluation. At last, through the review of the research methods in this field, the existing breast cancer research methods have been summarized, and the future developments are prospected.
乳腺癌是女性中发病率最高的癌症之一,乳腺癌的病理诊断可用于评估肿瘤的侵袭情况,为准确诊断和治疗提供重要信息。统计乳腺癌中有丝分裂细胞的数量是乳腺癌分裂的重要指标之一。本文综述了目前有丝分裂细胞检测的主流方法。这些方法主要是基于深度学习实现的,并对一些方法的结果进行了讨论、比较和评价。最后,通过对该领域研究方法的回顾,对现有乳腺癌研究方法进行了总结,并对未来的发展进行了展望。
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引用次数: 1
Deep Weighted Graph Embedding for Link Weight Prediction 链接权重预测的深度加权图嵌入
Zuo Wenbo, Liu Zhen
Graph structure is a widely existing data structure in real life. It has good modeling ability. Social networks, physical particles, texts, and so on, all can be represented as graph structure. Link prediction is a classical task in graph mining. This task uses the information of the observed network to predict missing links or possible new links between node pairs. Most of the existing studies are based on unweighted graphs. But in fact, lots of scenarios should be abstracted as weighted graphs, and the weight of links can reflect the strength of the ties between nodes. In this paper, we propose a deep weighted graph embedding method based on autoencoder and contrastive learning for link weight prediction on weighted graphs. Experiments on five real-world graph datasets demonstrate the effectiveness of our method.
图结构是现实生活中广泛存在的一种数据结构。具有良好的建模能力。社会网络、物理粒子、文本等等,都可以用图形结构表示。链接预测是图挖掘中的一项经典任务。该任务使用观察到的网络信息来预测节点对之间缺失的链路或可能出现的新链路。现有的大多数研究都是基于未加权的图。但实际上,很多场景都应该抽象为加权图,链路的权重可以反映节点之间联系的强度。本文提出了一种基于自编码器和对比学习的深度加权图嵌入方法,用于加权图的链接权重预测。在五个真实图形数据集上的实验证明了我们的方法的有效性。
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引用次数: 0
SAR Target Orientation Estimation Based on Manifold Learning 基于流形学习的SAR目标方向估计
Lou Jun, Wang Ling, Wang Pengyu
Target orientation estimation is an important step in synthetic aperture radar (SAR) automatic target recognition (ATR). In this paper, we propose a SAR target orientation estimation method using manifold learning. We analyze the low dimensional manifold of SAR targets with different orientation, and show that orientation angle can be estimated from the two dimensional embedding. Results in MSTAR data set are presented and show the validity of the proposed method.
目标方位估计是合成孔径雷达(SAR)自动目标识别(ATR)中的一个重要步骤。本文提出了一种基于流形学习的SAR目标方向估计方法。分析了不同方位的SAR目标的低维流形,证明了通过二维嵌入可以估计出方位角。在MSTAR数据集上的结果表明了该方法的有效性。
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引用次数: 0
Privacy-Preserving and Models Intrusion Detection Federated Deep Learning Challenges, Schemas and Future Trajectories 隐私保护和模型入侵检测联合深度学习的挑战、模式和未来轨迹
Yang Yu, Liao Jianping, Du Weiwei
Deep learning has made remarkable research advancements and wide-ranging applications in the domains of computer vision, multimodal, natural language processing, additionally, other areas. This has caused the academic community to pay increasingly close attention to the attack and defense technology in its training and testing phases, among which the federal deep learning has produced positive results. Federated deep learning models are prone to memorizing private and sensitive terminal participants' data, model parameters, when combined with the model's inherent vulnerability, they will result in privacy leakage, poisoning attack, model inference attack, adversarial attack. We briefly discuss the conception of federated deep learning as well as security challenges and open questions in this paper. In order to facilitate the understanding of these challenges and problems, we further propose a security system model. We also provide an overview and deduce the attack and mitigation approaches to the most sophisticated privacy-preserving and intrusion detection models. in the last two years. To tackle these challenges and enlighten further encryption techniques researches, finally, we discuss and describe current prospects and future trajectories of federated deep learning.
深度学习在计算机视觉、多模态、自然语言处理等领域取得了显著的研究进展和广泛的应用。这使得学术界对攻击防御技术在训练和测试阶段的关注日益密切,其中联邦深度学习已经取得了积极的成果。联邦深度学习模型容易记忆隐私和敏感的终端参与者的数据、模型参数,结合模型本身固有的脆弱性,会导致隐私泄露、中毒攻击、模型推理攻击、对抗性攻击。本文简要讨论了联邦深度学习的概念以及安全挑战和开放问题。为了便于理解这些挑战和问题,我们进一步提出了一个安全系统模型。我们还提供了一个概述,并推断出攻击和缓解最复杂的隐私保护和入侵检测模型的方法。在过去的两年里。为了解决这些挑战并启发进一步的加密技术研究,最后,我们讨论和描述了联邦深度学习的当前前景和未来轨迹。
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引用次数: 0
Design of 2-12 GHz Ultra-Wideband Band Pass Filter Using GAAS Integrated Passive Device Technology 基于GAAS集成无源器件技术的2- 12ghz超宽带通滤波器设计
Takele Yonas Mirete, Gebre Fisehatsion Mesfin, Meresa Girma Nigus, Tegegne Solomon Eshetie, Mengesha Yared Getachew, Molla Eldana Beyene
An Ultra-Wideband band pass filter (UWB-BPF) based on GaAs Technology is considered in this article. It is designed by cascading the High pass filter (HPF) and Low pass filters (LPF) with a transmission-zero out band rejection method. The two filters were designed with 5th order Chebyshev approach separately and then cascaded to get the desired band pass filter. To have a fast roll-off attenuation, out-of-band transmission zero is applied. Thus, a parallel resonance circuit is used. Moreover, L-network impedance matching has been introduced to enhance the input return loss. The design has been successfully realized in theory and also verified by its full layout EM simulation. The resulting UWB-BPF with 3.23 mm2 compact size provides 1.2 dB insertion loss, 134.6% fractional bandwidth, 78% selectivity factor, 0.094 ns group delay, and 16.2 dB return loss.
本文研究了一种基于GaAs技术的超宽带通滤波器(UWB-BPF)。它是用传输零输出带抑制方法将高通滤波器(HPF)和低通滤波器(LPF)级联设计的。两个滤波器分别采用5阶切比雪夫方法设计,然后级联得到期望的带通滤波器。为了有一个快速滚降衰减,带外传输零应用。因此,采用了并联谐振电路。此外,还引入了l -网络阻抗匹配来提高输入回波损耗。该设计已在理论上成功实现,并通过全版图电磁仿真得到了验证。所得到的UWB-BPF具有3.23 mm2的紧凑尺寸,具有1.2 dB插入损耗、134.6%分数带宽、78%选择性因子、0.094 ns群延迟和16.2 dB回波损耗。
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引用次数: 1
期刊
2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)
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