FLWD:A Webshell detection method based on federated learning by ZENG Qingpeng, CHAI Jiangli, WU Shuixiu

“…Experimental results on the AMWD’22 dataset show that the model’s accuracy is 99.47%, with an F1 score of 99.67%, indicating better detection performance compared to basic algorithm models and existing research algorithm models. …”
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Evaluating the Performance of SVM, Isolation Forest, and DBSCAN for Anomaly Detection by Lu Haowen

“…Identifying the most effective algorithm for anomaly detection is essential for enhancing nidustrial productivity. …”
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Unsupervised Detection of Suspicious Tissue Using Data Modeling and PCA by Ikhlas Abdel-Qader, Lixin Shen, Christina Jacobs, Fadi Abu Amara, Sarah Pashaie-Rad

“…Breast cancer is a major cause of death and morbidity among women all over the world, and it is a fact that early detection is a key in improving outcomes. Therefore development of algorithms that aids radiologists in identifying changes in breast tissue early on is essential. …”
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An optimization-inspired intrusion detection model for software-defined networking by Hui Xu, Longtan Bai, Wei Huang

“…This paper proposes an enhanced spider wasp optimizer (ESWO) algorithm for feature dimensionality reduction of intrusion detection datasets and constructs a new intrusion detection model (IDM), namely ESWO-IDM, for SDN. …”
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Study on the Lightweighting Strategy of Target Detection Model with Deep Learning by Junli Hu

“…Aiming at the high miss detection and false detection rate of traditional SSD (single shot multibox detector) target detection algorithm in target detection, this paper proposes a lightweight detection algorithm for deep learning target detection model in order to improve the detection accuracy. …”
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Detection of water surface targets based on improved Deformable DETR by Pengjiu WANG, Junbin Gong, Wei LUO, Xiao HUANG, Junjie GUO

“…However, conventional detection methods encounter several challenges, and existing deep-learning-based algorithms have limitations in this field, including limited datasets and insufficient detection speed even after improvement. …”
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Image Target Detection and Recognition Method Using Deep Learning by Hongyan Sun

“…Therefore, an image target detection and recognition algorithm based on the improved R-CNN network model is proposed. …”
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Aviation Rivet Classification and Anomaly Detection Based on Deep Learning by Xiao-bo Zhu

“…And a method of aviation rivet classification and anomaly detection based on deep learning algorithm was proposed. …”
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Detection and removal of “smacking” artefacts from lector speech records by Marek Jaskuła, Hanna Perużyńska

“…The algorithm performs detection of distortions in the time domain using differentiation of the signal. …”
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A novel transformer-based approach for cardiovascular disease detection by Nimra Noor, Muhammad Bilal, Saadullah Farooq Abbasi, Omid Pournik, Theodoros N. Arvanitis

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Spammer group detection based on cascading and clustering of core figures by Qianqian Jiang, Chunrong Zhang, Ning Li, Dickson K. W. Chiu, Xianwen Fang, Shujuan Ji

“…Thus, this research proposes a spammer group detection algorithm based on cascading and clustering of core figures. …”
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Local Outlier Detection Method Based on Improved K-means by Yu ZHOU, Hao XIA, Xuezhen YUE, Peichong WANG

“…Compared to the KNN and LOF algorithms, KLOD also demonstrates high accuracy in outlier detection. …”
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Seam-Carving forgery detection based on expanded Markov features by Guo-rui SHENG, Tie-gang GAO, Li FAN, Lin GAO, Fu-sheng YANG, Shun ZHANG

“…To deal with the digital image forgery using Seam-Carving, a detection algorithm based on expanded Markov features was proposed. …”
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Circle Detection with Adaptive Parameterization: A Bottom-Up Approach by Lin Han, Yan Zhuang, Ke Chen, Yuhua Xie, Guoliang Liao, Guangfu Yin, Jiangli Lin

“…This paper presents a novel circle detection algorithm based on two perceptually grounded parameters: the perceptual length difference resolution λ, derived from human cognitive models, and the minimum distinguishable distance threshold K, determined through empirical observations. …”
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Crowd abnormal behavior detection based on motion similar entropy by Fei LI, Ken CHEN, Meng LI, Chunmei GUO

“…It is an important research content of graphic processing in the field of intelligent video surveillance to detect abnormal events.An algorithm based on entropy of motion similarity (EMS) to detect abnormal behavior was proposed.Based on the optical flow algorithm,taking the bottom flow block as the basic unit to get the scene motion information,according to the concept of social network model,the construction scene of the motion network model (MNM) was proposed,the division of the scene particles motion similarity was completed,and the distribution EMS of MNM was calculated in the time domain.Finally,the obtained image entropy was compared with the reasonable threshold,to determine whether abnormal behavior occured.Experimental results indicate that the proposed algo-rithm can detect abnormal behavior effectively and show promising performance while comparing with the state of the art methods.…”
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Financial phishing detection method based on sensitive characteristics of webpage by Xiang-dong HU, Ke LIU, Feng ZHANG, Jia-fu LIN, Jun FU, Zhi-hui GUO

“…The method matches number of sensitive text using multiple pattern matching algorithm AC_SC (AC suitable for Chinese). Then, the method locates and cuts logo image of webpage, and utilizes PCA-SIFT algorithm to extract image features and match features with library of webpage logo which was established beforehand. …”
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Fractals and Independent Component Analysis for Defect Detection in Bridge Decks by Ikhlas Abdel-Qader, Fadi Abu-Amara, Osama Abudayyeh

“…Using Ground-Penetrating Radar (GPR) raw scans, this framework is composed of a feature extraction algorithm using fractals to detect defective regions and a deconvolution algorithm using banded-independent component analysis (ICA) to reduce overlapping between reflections and to estimate the radar waves travel time and depth of defects. …”
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A Method for Detecting Tomato Maturity Based on Deep Learning by Song Wang, Jianxia Xiang, Daqing Chen, Cong Zhang

“…The algorithm employs several technical means to improve detection accuracy and efficiency. …”
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Precision Detection of Infrared Small Target in Ground-to-Air Scene by Xiaona Dong, Huilin Jiang, Yansong Song, Keyan Dong

“…This paper proposes a non-window, structured algorithm for precision detection of infrared small targets under ground-to-air complex scenes. …”
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Alzheimer’s Disease Detection Using Deep Learning and Federated Learning by Taha Bin Niaz, Usman Amjad, Humera

“…The success and accuracy of the proposed algorithm are established with empirically defined metrics such as accuracy and defined thresholds. …”
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