Soft actor-critic algorithm and improved GNN model in secure access control of disaggregated optical networks by Zhenqian Zhao, Yuhe Wang

“…Additionally, it enables adaptive delineation of security boundaries across multiple domains through federated representation learning. Within this framework, the Soft Actor-Critic (SAC) algorithm is employed to construct a policy optimization mechanism. …”
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Deceptive Maneuvers: Subverting CNN-AdaBoost Model for Energy Theft Detection by Santosh Nirmal, Pramod Patil

“…Evasion attacks (EA) attempt to evade detection by misclassifying input data during testing. …”
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Remote Sensing Time Series Analysis: A Review of Data and Applications by Yingchun Fu, Zhe Zhu, Liangyun Liu, Wenfeng Zhan, Tao He, Huanfeng Shen, Jun Zhao, Yongxue Liu, Hongsheng Zhang, Zihan Liu, Yufei Xue, Zurui Ao

“…The high-frequency new data, i.e., a constellation strategy, increasing computing power and advancing deep learning algorithms, are driving a paradigm shift from traditional point-in-time mapping to near-real-time monitoring tasks, and even to modeling integration of parameter inversion and prediction in land, water, and air science. …”
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Enhancing Wildfire Detection via Trend Estimation Under Auto-Regression Errors by Xiyuan Liu, Lingxiao Wang, Jiahao Li, Khan Raqib Mahmud, Shuo Pang

“…Additionally, as a parametric method, the proposed algorithm can be applied to any time-related data, enabling the detection of underlying causes of trend changes for further analysis. …”
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Elevator fault precursor prediction based on improved LSTM-AE algorithm and TSO-VMD denoising technique. by Hao Cao, Xiaoyan Du

“…The robust capability of the VMD-BILSTM-AEAM algorithm to accurately process and analyze time-series data, even in the presence of noise, highlights its potential for broader applications in predictive maintenance and fault detection across various domains.…”
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Abnormal noise detection of electric machines based on HPSS-CIS and CNN-CBAM by Zhao Qingsong, Wang Xiufeng, Luo Kun, He Dan, Liu Xiang

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Incremental learning with SVM for multimodal classification of prostatic adenocarcinoma. by José Fernando García Molina, Lei Zheng, Metin Sertdemir, Dietmar J Dinter, Stefan Schönberg, Matthias Rädle

“…We propose a pattern recognition system with an incremental learning ensemble algorithm using support vector machines (SVM) tackling this problem employing multimodal MR images and a texture-based information strategy. …”
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Event‐triggered attack detection and state estimation based on Gaussian mixture model by Lu Jiang, Di Jia, Jiping Xu, Cui Zhu, Kun Liu, Yuanqing Xia

“…Then, inspired by the clustering algorithm in machine learning, a detection mechanism based on Gaussian mixture model, which can set a confidence level for the measurement of each sensor is proposed. …”
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ML-based Plant Stress Detection from IoT-sensed Reduced Electromes by Marcos De Oliveira Jr, Gregory Sedrez, Gerson Geraldo H. Cavalheiro

“…The use of Internet of Things (IoT) devices and Machine Learning (ML) techniques has automated and enhanced data collection and classification, helping researchers identify behaviors and classify them to detect plant stress. …”
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A New Mask R-CNN-Based Method for Improved Landslide Detection by Silvia Ullo, Amrita Mohan, Alessandro Sebastianelli, Shaik Ahamed, Basant Kumar, Ramji Dwivedi, Ganesh R. Sinha

“…This article presents a novel method of landslide detection by exploiting the Mask R-CNN capability of identifying an object layout by using a pixel-based segmentation, along with transfer learning used to train the proposed model. …”
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Pesticide Residue Detection in Broccoli Based on Hyperspectral Technology and Convolutional Neural Network by Dan WANG, Yuqing LUAN, Zuojun TAN, Wei WEI

“…Using broccoli as a sample, this article used hyperspectral technology combined with machine learning algorithms and deep learning algorithms to provide a simple, fast, low-cost, and non-destructive method for detecting pesticide residues in broccoli. …”
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Leveraging machine learning to proactively identify phishing campaigns before they strike by Kun Zhang, Haifeng Wang, Meiyi Chen, Xianglin Chen, Long Liu, Qiang Geng, Yu Zhou

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AI Driven Fraud Detection Models in Financial Networks: A Comprehensive Systematic Review by Nusrat Jahan Sarna, Farzana Ahmed Rithen, Umme Salma Jui, Sayma Belal, Al Amin, Tasnim Kabir Oishee, A. K. M. Muzahidul Islam

“…Future research should focus on improving the transparency of the AI model, integrating AI with blockchain for secure data sharing, and leveraging federated learning to enhance fraud detection capabilities. …”
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Detection of AI-Generated Texts: A Bi-LSTM and Attention-Based Approach by John Blake, Abu Saleh Musa Miah, Krzysztof Kredens, Jungpil Shin

“…This paper presents a novel algorithm that leverages cutting-edge machine-learning techniques to accurately and efficiently detect AI-generated texts. …”
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A Novel Metaheuristic-Based Methodology for Attack Detection in Wireless Communication Networks by Walaa N. Ismail

“…In this study, we explore the application of an adaptive optimized machine learning-based framework to improve intrusion detection system (IDS) performance in wireless network access scenarios. …”
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Real Time Intrusion Detection System Based on Web Log File Analysis by Rawand Raouf Abdalla, Alaa Khalil Jumaa, Ahmad Freidoon Fadhil

“…Real-time cyberattacks are common, and any delay in detection can lead to serious consequences like data breaches and system outages. …”
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A Deep Learning Biomimetic Milky Way Compass by Yiting Tao, Michael Lucas, Asanka Perera, Samuel Teague, Timothy McIntyre, Titilayo Ogunwa, Eric Warrant, Javaan Chahl

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Proposing Smart System for Detecting and Monitoring Vehicle Using Multiobject Multicamera Tracking by Phat Nguyen Huu, Bang Nguyen Anh, Quang Tran Minh

“…Our system leverages data collected from traffic surveillance cameras and harnesses the power of deep learning technology to detect and track vehicles smoothly. …”
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Microwave Tomography System for Methodical Testing of Human Brain Stroke Detection Approaches by Ilja Merunka, Andrea Massa, David Vrba, Ondrej Fiser, Marco Salucci, Jan Vrba

“…It is therefore suitable for large-scale measurements with high variability of measured data for stroke detection and classification based on machine learning methods. …”
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Detection of Critical Parts of River Crab Based on Lightweight YOLOv7-SPSD by Guoai Fang, Yu Zhao

“…In this paper, we propose a lightweight deep learning model called YOLOv7-SPSD for detecting river crab tails. …”
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