Results 31 to 40 of about 108,365 (267)
Comparative Analysis of Anomaly Detection Techniques Using Generative Adversarial Network
Sir Syed University Research Journal of Engineering and Technology, 2023 Anomaly detection in a piece of data is a challenging task. Researchers use different approaches to classify data as anomalous. These include traditional, supervised, unsupervised, and semi-supervised techniques.
Imran Ullah Khan +4 more
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Advanced Engineering Materials, EarlyView.A wood‐based magnetic and conductive material called Magwood (MW), capable of blocking almost 99.99% of electromagnetic waves (in the X‐band frequency range), is synthesized using a simple, solvent‐free process. MW is lightweight, resists water, and is flame‐retardant, making it a promising alternative for shielding electronics. The rapid proliferation
Akash Madhav Gondaliya +3 more
wiley +1 more source
Hybrid Discriminator With Correlative Autoencoder for Anomaly Detection
IEEE Access, 2021 Advances in deep neural networks (DNNs) have led to impressive results and in recent years many works have exploited DNNs for anomaly detection. Among others, generative/reconstruction model-based methods have been frequently used for anomaly detection ...
Jungeon Lee +2 more
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Advanced Functional Materials, EarlyView.A lack of standard approaches for testing and reporting the performance of metal halide perovskites and organic semiconductor radiation detectors has resulted in inconsistent interpretation of performance parameters, impeding progress in the field. This Perspective recommends key metrics and experimental details, which are suggested for reporting in ...
Jessie A. Posar +8 more
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Anomaly Detection Using Graph Anomaly Rules
Big Data Mining and AnalyticsAnomaly detection in attribute networks is utilized to discover patterns of individuals or groups that deviate from the majority, and is widely used in areas such as e-commerce and social media.
Bowen Dong +4 more
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Hyperspectral Anomaly Detection Method Based on Low Rank Total Variation Regu-larization
Jisuanji kexue yu tansuo, 2020 Hyperspectral remote sensing technology provides abundant spectral information for exploring objects and supplies a better data source for anomaly detection.
XU Chao, ZHAN Tianming
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Anomaly detection has become one of the crucial tasks in hyperspectral images processing. However, most deep learning-based anomaly detection methods often suffer from the incapability of utilizing spatial–spectral information, which decreases the
Song Xiao +5 more
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Real-time monitoring of COVID-19 dynamics using automated trend fitting and anomaly detection [PDF]
, 2021 Thibaut Jombart +16 more
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Advanced Functional Materials, EarlyView.A spin group (SG)‐based mechanism is proposed to realize a single pair of Weyl points. PT‐symmetric nodal lines (NLs) persist under T‐breaking, protected by the combination of SG and P symmetry. When considering spin‐orbit coupling, the SG‐protected NL will split into Weyl points, which will also induce anomalous transport phenomena arising from ...
Shifeng Qian +6 more
wiley +1 more source
Surface anomaly detection on island-based PV panels using edge neural networks
Zhejiang dianliSurface anomaly detection on photovoltaic （PV） panels is crucial for their operation and maintenance， especially in island environments where challenges such as small anomaly sizes and minimal color differences are prevalent. Due to the poor accuracy and
ZHANG Yinxian, ZHANG Zhanyao, ZHANG Xiya
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