Pub Date : 2022-12-16DOI: 10.1109/ICCWAMTIP56608.2022.10016612
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.
{"title":"Pixel-Level Feature Clustering Learning for Image Anomaly Detection and Localization","authors":"Huang Chao","doi":"10.1109/ICCWAMTIP56608.2022.10016612","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP56608.2022.10016612","url":null,"abstract":"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.","PeriodicalId":159508,"journal":{"name":"2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132336032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-16DOI: 10.1109/ICCWAMTIP56608.2022.10016476
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.
{"title":"Joint Positioning of Two Nodes via Direction Finding of Signals of Opportunity and Cooperative Range Measurement","authors":"Junlin Li, R. Chen, Xiangyu Peng, Wenrong Chen, Xinyu Hu, Q. Wan","doi":"10.1109/ICCWAMTIP56608.2022.10016476","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP56608.2022.10016476","url":null,"abstract":"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.","PeriodicalId":159508,"journal":{"name":"2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)","volume":"182 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134554317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-16DOI: 10.1109/ICCWAMTIP56608.2022.10016541
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.
{"title":"A Polarization-Independent Transmissive Metalens In The Microwave Band","authors":"Wang Ling, Yang Xishu, G. Feng, Teng Shuhua, Tan Zhiguo, Zhang Xing, Lou Jun","doi":"10.1109/ICCWAMTIP56608.2022.10016541","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP56608.2022.10016541","url":null,"abstract":"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.","PeriodicalId":159508,"journal":{"name":"2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132877595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-16DOI: 10.1109/ICCWAMTIP56608.2022.10016500
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.
{"title":"Research on Security Technology of Sensing Terminal of Internet of Things","authors":"Li Xianli, Pan Wei, Wang Yisheng, Li Ming, Liu Guosong","doi":"10.1109/ICCWAMTIP56608.2022.10016500","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP56608.2022.10016500","url":null,"abstract":"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.","PeriodicalId":159508,"journal":{"name":"2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131678434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-16DOI: 10.1109/ICCWAMTIP56608.2022.10016537
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.
{"title":"A Chaos-Based and Ensembled Method for Outlier Detection","authors":"Li Wei","doi":"10.1109/ICCWAMTIP56608.2022.10016537","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP56608.2022.10016537","url":null,"abstract":"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.","PeriodicalId":159508,"journal":{"name":"2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133973791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-16DOI: 10.1109/ICCWAMTIP56608.2022.10016492
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.
{"title":"Deep Learning Techniques for Breast Cancer Mitotic Cell Detection","authors":"Jiquan Li, Laixiang Qiu, Yujun Yang, Wang Zhou","doi":"10.1109/ICCWAMTIP56608.2022.10016492","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP56608.2022.10016492","url":null,"abstract":"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.","PeriodicalId":159508,"journal":{"name":"2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)","volume":"213 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134439043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-16DOI: 10.1109/ICCWAMTIP56608.2022.10016532
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.
{"title":"Deep Weighted Graph Embedding for Link Weight Prediction","authors":"Zuo Wenbo, Liu Zhen","doi":"10.1109/ICCWAMTIP56608.2022.10016532","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP56608.2022.10016532","url":null,"abstract":"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.","PeriodicalId":159508,"journal":{"name":"2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122234795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-16DOI: 10.1109/ICCWAMTIP56608.2022.10016516
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.
{"title":"SAR Target Orientation Estimation Based on Manifold Learning","authors":"Lou Jun, Wang Ling, Wang Pengyu","doi":"10.1109/ICCWAMTIP56608.2022.10016516","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP56608.2022.10016516","url":null,"abstract":"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.","PeriodicalId":159508,"journal":{"name":"2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123298812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-16DOI: 10.1109/ICCWAMTIP56608.2022.10016548
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.
{"title":"Privacy-Preserving and Models Intrusion Detection Federated Deep Learning Challenges, Schemas and Future Trajectories","authors":"Yang Yu, Liao Jianping, Du Weiwei","doi":"10.1109/ICCWAMTIP56608.2022.10016548","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP56608.2022.10016548","url":null,"abstract":"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.","PeriodicalId":159508,"journal":{"name":"2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125213228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"Design of 2-12 GHz Ultra-Wideband Band Pass Filter Using GAAS Integrated Passive Device Technology","authors":"Takele Yonas Mirete, Gebre Fisehatsion Mesfin, Meresa Girma Nigus, Tegegne Solomon Eshetie, Mengesha Yared Getachew, Molla Eldana Beyene","doi":"10.1109/ICCWAMTIP56608.2022.10016577","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP56608.2022.10016577","url":null,"abstract":"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.","PeriodicalId":159508,"journal":{"name":"2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121958067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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