Machine Learning- and Deep Learning-Based Multi-Model System for Hate Speech Detection on Facebook by Amna Naseeb, Muhammad Zain, Nisar Hussain, Amna Qasim, Fiaz Ahmad, Grigori Sidorov, Alexander Gelbukh

“…The ML algorithms used in this study are LR, SVM, RF, NB, KNN, and GBM. …”
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Cross-Modal Fake News Detection Method Based on Multi-Level Fusion Without Evidence by Ping He, Hanxue Zhang, Shufu Cao, Yali Wu

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Environmental Sensitivity in AI Tree Bark Detection: Identifying Key Factors for Improving Classification Accuracy by Charles Warner, Fanyou Wu, Rado Gazo, Bedrich Benes, Songlin Fei

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Novel topic detection method for microblog based on SVM filtration by Jun-xia CHENG, Zhi-tang LI, Ming-guang ZOU, Jin XIAO

“…A detection method based on SVM filtration was proposed.The method uses text feature as imported vectors to filtrate microblog news,reducing the amount of calculation greatly.A single-pass clustering algorithm based on the improvement of high-frequency words sorting was proposed,which can detect isolated points commendably.Experimental results show that the method can detect news topics from massive microblog data efficiently.…”
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High-Precision Centroid Localization Algorithm for Star Sensor Under Strong Straylight Condition by Jindong Yuan, Junfeng Wu, Guohua Kang

“…The results show that the proposed algorithm outperforms the TOP-HAT, MAX-BACKG (Max-Background Filtering), LCM (Local Contrast Measure), MPCM (Multiscale Patch-Based Contrast Measure), and CMLCM (Curvature-Based Multidirectional Local Contrast Method for Star Detection of Star Sensor) algorithms in terms of star point detection rate. …”
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An Anomaly Detection Method for Multivariate Statistical Process Based on POT by Dazhi ZHANG, Xiaoyu LUO, Sheng ZHENG

“…Considering the limitations of fixed thresholds and manual detection methods, which are difficult to adapt to the dynamic changes in time series data, this paper proposes an anomaly detection method based on peaks-over-threshold (POT) algorithm for multivariate statistical processes. …”
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Out-of-hospital multimodal seizure detection: a pilot study by Martin Ballegaard, Troels Wesenberg Kjær, Ivan Chrilles Zibrandtsen, Jonas Munch Nielsen, Ástrós Eir Kristinsdóttir, Paolo Masulli, Tobias Søren Andersen

“…A support vector machine based seizure detection algorithm was applied using both in-patient seizures and out-of-hospital electrographic seizures in one patient. …”
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Research on lightweight tunnel cable fire recognition algorithm based on multi-scale features by Zimeng Liu, Lei Zhang, Huiqiang Ma, Xuebing Chen, Molin Zhang

“…In this study, a lightweight YOLO-v5 tunnel cable fire recognition algorithm with multiscale features is proposed. By replacing the YOLO-v5 backbone network, Darknet53, with Mobilenetv3-small and integrating the SimAM attention mechanism, the lightweight and detection speed of the network was improved. …”
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Matrix Camera, Composed Television System for the Detection of the Contact Wire by V. I. Sirotinin, P. V. Stolbov, A. V. Voronin

“…A method for increasing the efficiency of the contact wire detection system by upgrading hardware and software elements of the system is presented. …”
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A lightweight personnel detection method for underground coal mines by Shuai WANG, Wei YANG, Yuxiang LI, Jiaqi WU, Wei YANG

“…Commonly used detection algorithms have large parameter counts, high requirements on equipment arithmetic, and are not satisfactory for application in low illumination environments in coal mines. …”
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Detection, Reconstruction, and Repairing the Distortion in the Quran Pages Based on Watermarking by Afsaneh Arabzadeh, AliReza Naghsh

“…The watermarking algorithm in this method is able to recover distortions in addition to detecting them.…”
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Anomaly detection of large scale network based on data streams by ZHENG Jun, HU Ming-zeng, YUN Xiao-chun, ZHENG Zhong

“…The anomaly detection algorithms of the large scale network（LSN） were required to analysis the vast network traffic of G bit level in real-time and on-the-fly.A novel monitoring mechanism of LSN anomaly detection based on the data stream approach was proposed.The main contributions included: the sketch data structure and the frequent sketch algorithm of data streams were designed for anomaly detection of LSN.Optimized query methods were designed for customizing the security monitoring and detection policy with the correlations of multi data streams.The data reduction was proposed to make it possible that the whole network traffic character could be got using a few of special data streams.The experiments of the real networking environments validate the effectivity of LSN anomaly detection methods.…”
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Research on system log anomaly detection based on deep learning by Yidong WANG, Peishun LIU, Gbin WAN

“…The system log reflects the running status of the system and records the activity information of specific events in the system.Therefore,the rapid and accurate detection of the system abnormal log is important to the security and stability of the system.A log anomaly detection algorithm based on GRU neural network is proposed.Log parsing is implemented based on log key technology.Log anomaly detection is realized by using anomaly detection model of execution path and anomaly detection model of parameter value.The system has the advantages of less parameters and faster training.It improves the running speed while achieving higher detection accuracy,and is suitable for log analysis of large information systems.…”
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Unsupervised Salient Object Detection by Aggregating Multi-Level Cues by Chenxing Xia, Hanling Zhang

“…Extensive experimental results demonstrate that the proposed algorithm performs favorably against the state-of-art saliency detection methods in terms of different evaluation metrics on several benchmark datasets.…”
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Detection and Classification of Single Machining Error of Non-circular Gear by Dai Jianqing, Wang Shengze

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Research progress of abnormal user detection technology in social network by Qiang QU, Hongtao YU, Ruiyang HUANG

“…In social networks,the problem of anomalous users detection is one of the key problems in network security research.The anomalous users conduct false comments,cyberbullying or cyberattacks by creating multiple vests,which seriously threaten the information security of normal users and the credit system of social networks ,so a large number of researchers conducted in-depth study of the issue.The research results of the issue in recent years were reviewed and an overall structure was summarized.The data collection layer introduces the data acquisition methods and related data sets,and the feature presentation layer expounds attribute features,content features,network features,activity features and auxiliary features.The algorithm selection layer introduces supervised algorithms,unsupervised algorithms and graph algorithms.The result evaluation layer elaborates the method of data annotation method and index.Finally,the future research direction in this field was looked forward.…”
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An Innovative Approach for Fake News Detection using Machine Learning by Maya Hisham, Raza Hasan, Saqib Hussain

“…Various text feature extraction techniques and classification algorithms are reviewed, with the Support Vector Machine (SVM) linear classification algorithm using TF-IDF feature extraction achieving the highest accuracy of 99.36%. …”
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MIMO Detection for High Order QAM by Canonical Dual Approach by Ye Tian, Jr-Fong Dang

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Anomaly detection of large scale network based on data streams by ZHENG Jun, HU Ming-zeng, YUN Xiao-chun, ZHENG Zhong

“…The anomaly detection algorithms of the large scale network（LSN） were required to analysis the vast network traffic of G bit level in real-time and on-the-fly.A novel monitoring mechanism of LSN anomaly detection based on the data stream approach was proposed.The main contributions included: the sketch data structure and the frequent sketch algorithm of data streams were designed for anomaly detection of LSN.Optimized query methods were designed for customizing the security monitoring and detection policy with the correlations of multi data streams.The data reduction was proposed to make it possible that the whole network traffic character could be got using a few of special data streams.The experiments of the real networking environments validate the effectivity of LSN anomaly detection methods.…”
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Coal mine conveyor monitoring video enhancement algorithm based on DP-YOLOv7 by Lei ZHANG

“…Aiming at the problems encountered by video surveillance during the operation of belt conveyor, such as insufficient light, moisture and large coal dust pollution, a new DP-YOLOv7 video detection algorithm for coal mine belt conveyor is proposed based on YOLOv7 target detection algorithm. …”
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