Detection Method for Islanded Microgrid Based on the Local Detection Method by Zhongqiang LIU, Zhongfu LIU

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Polarization optical detection and localization of subcutaneous lesions by Xinxian Zhang, Jiahao Fan, Jiawei Song, Nan Zeng, Honghui He, Valery V. Tuchin, Hui Ma

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Anomaly Detection and Localization via Graph Learning by Olabode Amusan, Di Wu

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Robust tampering detection and localization of composite image by Xiao WANG, Rong ZHANG, Lijun GUO

“…Aiming at the problem of tamper detection of composite image of natural images and highly simulated computer-generated images,a method of extracting image block color and texture feature based on differential histogram and local binary texture descriptor in YCbCr color space was proposed.By training posterior probability support vector machine,the image block to be measured was identified.In the case of non-overlapping block,the approximate tampering area was general judged,then the block was discriminated by pixel in the region,ultimately the accurate location of tampering area was achieved.The experimental results show that the recognition rate of 128 dpi×128 dpi image blocks is 94.75%,which is higher than other methods.The tapering region of the synthesized image can be precisely positioned,and the rotation and scaling operation show good coercivity.…”
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A Shield Segment Bolt Detection and Localization Method Based on Ellipse Detection by Jie Liu, Shuaishuai Liu, Zhendong He, Yanqiu Xiao, Guangzhen Cui, Pengpeng Wang

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Local Community Detection Algorithm Based on Minimal Cluster by Yong Zhou, Guibin Sun, Yan Xing, Ranran Zhou, Zhixiao Wang

“…In order to discover the structure of local community more effectively, this paper puts forward a new local community detection algorithm based on minimal cluster. …”
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Research status of community detection based on local expansion by Yancui SHI, Yuan WANG, Qing ZHAO, Xiankun ZHANG

Subjects: “…social network;community detection;selection of seeds;local expansion…”
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Nonnegative Matrix Factorizations Performing Object Detection and Localization by G. Casalino, N. Del Buono, M. Minervini

“…We study the problem of detecting and localizing objects in still, gray-scale images making use of the part-based representation provided by nonnegative matrix factorizations. …”
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AI-Assisted Detection and Localization of Spinal Metastatic Lesions by Edgars Edelmers, Artūrs Ņikuļins, Klinta Luīze Sprūdža, Patrīcija Stapulone, Niks Saimons Pūce, Elizabete Skrebele, Everita Elīna Siņicina, Viktorija Cīrule, Ance Kazuša, Katrina Boločko

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Robust Corner Detection Using Local Extrema Differences by Reza Yazdi, Hassan Khotanlou, Hosna Khademfar

“…It achieves better accuracy in corner localization and reduces both missed detections and false positives. …”
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Framework for mobility model detection based on local information by PENG Min, HONG Pei-lin, LU Han-cheng, XUE Kai-ping

“…In order to get the real-time mobility model information which could be exploited to assist routing decision,a framework for mobility model detection based on local information（FMDL） was proposed.In FMDL,each node collected the local information on connectivity through neighbor discovery mechanism and generated the connectivity matrix.The changing rule of relative position could be extracted from the connectivity matrix,and then the real-time mobility model was detected.The simulation results show that FMDL achieves high detection rate without any auxiliary equipment.…”
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Multi-branch network for double JPEG detection and localization by Ahmed M. Fouad, Hala H. Zayed, Ahmed Taha

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Detection of polysaccharides from local algae in fresh water by Nawras Al-Rikabi, Roa'a Jaafar Khairallah

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Detection and Localization of Stationary Waves on Venus Using a Self‐Supervised Anomaly Detection Model by Husnu Baris Baydargil, Jose Eduardo Oliveira Silva, Yeon Joo Lee, Meeyoung Cha

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Fault Detection Based on Kernel Global Local Preserving Projection by Wenbiao Wang, Qianqian Zhang, Youwei Hao

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Abnormal link detection algorithm based on semi-local structure by Haoran SHI, Lixin JI, Shuxin LIU, Gengrun WANG

“…With the research in network science, real networks involved are becoming more and more extensive.Redundant error relationships in complex systems, or behaviors that occur deliberately for unusual purposes, such as wrong clicks on webpages, telecommunication network spying calls, have a significant impact on the analysis work based on network structure.As an important branch of graph anomaly detection, anomalous edge recognition in complex networks aims to identify abnormal edges in network structures caused by human fabrication or data collection errors.Existing methods mainly start from the perspective of structural similarity, and use the connected structure between nodes to evaluate the abnormal degree of edge connection, which easily leads to the decomposition of the network structure, and the detection accuracy is greatly affected by the network type.In response to this problem, a CNSCL algorithm was proposed, which calculated the node importance at the semi-local structure scale, analyzed different types of local structures, and quantified the contribution of edges to the overall network connectivity according to the semi-local centrality in different structures, and quantified the reliability of the edge connection by combining with the difference of node structure similarity.Since the connected edges need to be removed in the calculation process to measure the impact on the overall connectivity of the network, there was a problem that the importance of nodes needed to be repeatedly calculated.Therefore, in the calculation process, the proposed algorithm also designs a dynamic update method to reduce the computational complexity of the algorithm, so that it could be applied to large-scale networks.Compared with the existing methods on 7 real networks with different structural tightness, the experimental results show that the method has higher detection accuracy than the benchmark method under the AUC measure, and under the condition of network sparse or missing, It can still maintain a relatively stable recognition accuracy.…”
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Unsupervised Anomaly Detection of Forceps Force by Localizing the Region of Interest by Wenhui Zhuang, Kimihiko Masui, Naoto Kume, Megumi Nakao

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Erasure conversion in Majorana qubits via local quasiparticle detection by Abhijeet Alase, Kevin D. Stubbs, Barry C. Sanders, David L. Feder

“…This work tackles the errors originating from intrinsically excited quasiparticles by developing an erasure conversion scheme based on local quasiparticle detection. To model such measurements, we begin by constructing the quasiparticle position operator for the Kitaev chain. …”
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Advances in Object Detection and Localization Techniques for Fruit Harvesting Robots by Xiaojie Shi, Shaowei Wang, Bo Zhang, Xinbing Ding, Peng Qi, Huixing Qu, Ning Li, Jie Wu, Huawei Yang

Subjects: “…object detection…”
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Detection of Gene Localization in a Large Concomitant Strabismus Family by Kadriye Erkan Turan, Emin Cumhur Şener, Ali Şefik Sanaç

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