Anomaly detection model for multivariate time series based on stochastic Transformer by Weigang HUO, Rui LIANG, Yonghua LI

“…Aiming at the problem that the existing multivariate time series anomaly detection models based on variational autoencoders could not propagate long-term temporal dependencies between stochastic variables in latent space, the stochastic Transformer for MTS anomaly detection (ST-MTS-AD) model which combined Transformer encoder with VAE was proposed.In the inference network of the ST-MTS-AD, the MTS long-term temporal dependent features generated by Transformer encoder and the sampled values of the stochastic variables at the previous moment were inputted into the multilayer perceptron, the approximate posterior distribution of the stochastic variables at the current moment was generated by the multilayer perceptron, and the temporal dependencies between stochastic variables were realized.The gated transition function(GTF) was used to generate the prior distribution of stochastic variables.The generation network of the ST-MTS-AD reconstructed the distribution of the MTS values at each moment by the multilayer perceptron whose input was the MTS long-term temporal dependent features generated by the inference network and the approximate posterior sampling values of stochastic variables.The distribution of normal MTS dataset was learned by the variational inference technology, and the abnormal MTS segment was determined by the log-likelihood of the reconstruction probability.Experiments on four public datasets show that the ST-MTS-AD model significantly improves the F1 score over the typical baseline models.…”
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A Two-Stage Compression Method for the Fault Detection of Roller Bearings by Huaqing Wang, Yanliang Ke, Ganggang Luo, Lingyang Li, Gang Tang

“…Second, a fault detection scheme based on the compressed sensing is applied to extract the fault features, which can compress the symptom parameter wave thoroughly with a random matrix called the measurement matrix. …”
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OBJECT DETECTION METHOD APPLICATION TO RUNWAY IMAGERY IN LOW VISIBILITY CONDITIONS by D. S. Andreev

“…The covered methods solve the problem of detecting objects of the runway in low visibility conditions for static image. …”
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An Effective Hybrid Deep Neural Network for Arabic Fake News Detection by Tahseen A. Wotaifi, Ban N. Dhannoon

“…It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. …”
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Comparative Analysis of Machine Learning Based Approaches for Face Detection and Recognition by Ratnesh Kumar Shukla, Arvind Kumar Tiwari

“…This article discusses a device focused on images that enables users to recognise and detect many face-related features using the webcam. …”
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Bottom Detection Method of Side-Scan Sonar Image for AUV Missions by Huapeng Yu, Ziyuan Li, Dailin Li, Tongsheng Shen

“…To address this problem, this study proposes an automatic detection method for the sea bottom line based on the actual experimental acquisition of SSS images, which is supposed to support the autonomous underwater vehicle (AUV) for intelligent target detection and classification. …”
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Research on dust identification and concentration detection method based on machine vision by Luyang TU, Qinghua CHEN, Yingsong CHENG, Bingyou JIANG

“…Aiming at the problem that the current machine vision algorithm fails to combine position information with concentration value in the field of dust detection, we propose an algorithm that combines improved YOLOv5 with multivariate model. …”
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CFR-YOLO: A Novel Cow Face Detection Network Based on YOLOv7 Improvement by Guohong Gao, Yuxin Ma, Jianping Wang, Zhiyu Li, Yan Wang, Haofan Bai

“…In order to solve these problems, this study explores the application of cattle face detection technology in cattle individual detection to improve the accuracy of detection, an approach that is particularly important in smart animal husbandry and animal behavior analysis. …”
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Web Application Firewall Based on Anomaly Detection using Deep Learning by Sezer Toprak, Ali Gökhan Yavuz

“…Anomaly detection has been researched in different areas and application domains. …”
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Iterative PolInSAR Target Decomposition for Scattering Characterization and Building Detection by Di Zhuang, Lamei Zhang, Bin Zou

“…To handle this problem, an iterative polarimetric interferometric synthetic aperture radar (PolInSAR) target decomposition method for scattering characterization and building detection is proposed in this article, and it consists of three key components. …”
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Anomaly Detection in Health Insurance Claims Using Bayesian Quantile Regression by Ezekiel N. N. Nortey, Reuben Pometsey, Louis Asiedu, Samuel Iddi, Felix O. Mettle

“…It is therefore imperative to analyze health insurance claim data to identify potentially suspicious claims. Typically, anomaly detection can be posited as a classification problem that requires the use of statistical methods such as mixture models and machine learning approaches to classify data points as either normal or anomalous. …”
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A Benchmark Dataset for Aircraft Detection in Optical Remote Sensing Imagery by Jianming Hu, Xiyang Zhi, Bingxian Zhang, Tianjun Shi, Qi Cui, Xiaogang Sun

“…The problem is that existing aircraft detection datasets rarely simultaneously consider the diversity of target features and the complexity of environmental factors, which has become an important factor restricting the effectiveness and reliability of aircraft detection algorithms. …”
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Gonorrhea in the Russian Federation: incidence, active case detection and laboratory diagnostics by Elena V. Bogdanova, Nikita Yu. Nosov, Xenia I. Plahova

“…Gonorrhea is a possible cause of pelvic inflammatory complications, reproductive health disorders and adverse pregnancy outcomes. The problem of gonococcal antimicrobial resistance remains actual. …”
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Botnet detection in internet of things using stacked ensemble learning model by Mudasir Ali, Muhammad Faheem Mushtaq, Urooj Akram, Daniel Gavilanes Aray, Manuel Masias Vergara, Hanen Karamti, Imran Ashraf

“…Despite existing approaches for cyber attack detection, botnets prove to be a particularly difficult problem that calls for more advanced detection methods. …”
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Automatic Detection and Unsupervised Clustering-Based Classification of Cetacean Vocal Signals by Yinian Liang, Yan Wang, Fangjiong Chen, Hua Yu, Fei Ji, Yankun Chen

“…To extract useful features from a large amount of PAM data for classifying different cetacean species, we propose an automatic detection and unsupervised clustering-based classification method for cetacean vocal signals. …”
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Blockchain-Enabled Deep Recurrent Neural Network Model for Clickbait Detection by Abdul Razaque, Bandar Alotaibi, Munif Alotaibi, Fathi Amsaad, Ansagan Manasov, Salim Hariri, Banu B. Yergaliyeva, Aziz Alotaibi

“…The clickbait search process is accomplished by incorporating the binary search features for a faster and more efficient search process for malicious content-detection. …”
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Detecting faults in electronic combustion engine control systems by acoustic parameters by V. D. Gabidulin, V. N. Dobromirov

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Improved Hypernymy Detection Algorithm Based on Heterogeneous Graph Neural Network by Li Ren, Jing Huang, Hai-Tao Jia, Shu-Bao Sun, Kai-Shi Wang, Yi-Le Wu

“…The representation of relation nodes is modified by encoding relation definitions through a pre-trained model, enabling the model to understand the semantic relations between concept nodes. To address the problem of overfitting in traditional graph attention networks, the calculation order of adjacency node aggregation is changed in the heterogeneous graph to capture dynamic attention features. …”
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An Explainable Deep Learning Network for Environmental Microorganism Classification Using Attention-Enhanced Semi-Local Features by R. Karthik, Armaano Ajay, Akshaj Singh Bisht, Jaehyuk Cho, V. E. Sathishkumar

“…Deep learning (DL) offers a more efficient and accurate solution to this problem by automating the detection and classification of EMs. …”
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ULTRASONIC SIGNAL FEATURE EXTRACTION METHOD BASED ON GENERAL CROSS-VALIDATION THRESHOLDING IN SYNCHROSQUEEZING WAVELET DOMAIN by XIAO ChangMing, XIAO Han, YI CanCan

“…Using ultrasonic non-destructive testing technology,when detecting the surface crack of the shaft,the micro crack echo signal is often covered by various noises,which causes the crack to be unrecognizable and positioned. …”
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