LI-YOLO: An Object Detection Algorithm for UAV Aerial Images in Low-Illumination Scenes by Songwen Liu, Hao He, Zhichao Zhang, Yatong Zhou

“…Aiming at the problem of low brightness, high noise, and obscure details of low-illumination images, an object detection algorithm, LI-YOLO (Low-Illumination You Only Look Once), for UAV aerial images in low-illumination scenes is proposed. …”
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Infrared Image Classification and Detection Algorithm for Power Equipment Based on Improved YOLOv10 by Xiu Ji, Zheyu Yue, Hongliu Yang, Zehong Zhang

“…However, infrared imaging technology has shortcomings such as poor signal clarity and serious background noise interference. To address this problem, this paper proposes an infrared image classification and detection algorithm for power equipment based on the improved YOLOv10, named YOLOv10plus. …”
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Detection algorithm for wearing safety helmet under mine based on improved YOLOv5s by Yuanbin WANG, Sixiong WEI, Huaying WU, Yu DUAN, Meng LIU

“…Aiming at the problems of low accuracy and high missed detection rate of personnel safety helmet detection algorithm caused by complex environment under mine, an improved mine safety helmet detection algorithm based on YOLOv5s is proposed. …”
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A High-Accuracy Underwater Object Detection Algorithm for Synthetic Aperture Sonar Images by Jiahui Su, Deyin Xu, Lu Qiu, Zhiping Xu, Lixiong Lin, Jiachun Zheng

“…To improve these problems, this paper proposes a high-accuracy underwater object detection algorithm for SAS images, named the HAUOD algorithm. …”
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Distributed denial-of-service (DDOS) attack detection using supervised machine learning algorithms by S. Abiramasundari, V. Ramaswamy

“…DDoS attacks need to be detected since they cause serious problems. Supervised machine learning models are effective mechanisms for detecting DDoS attacks. …”
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Hypertension Detection Using Passive-Aggressive Algorithm With The PA-I And PA-II Methods by M. Hafidz Ariansyah, Sri Winarno

“…This algorithm can work well for learning by transforming data and dealing with unbalanced classification problems. …”
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Target Detection Algorithm Based on Global Feature Fusion in Parallel Dual Path Backbone by QIU Yunfei, XIN Hao

“…At the same time, simply adding or splicing feature pyramids is not conducive to the integration of shallow to deep features. To solve these problems, a target detection algorithm based on global feature fusion in parallel dual path backbone is proposed. …”
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CF-YOLO for small target detection in drone imagery based on YOLOv11 algorithm by Chengcheng Wang, Yuqi Han, Chenggui Yang, Mingjie Wu, Zaiqing Chen, Lijun Yun, Xuesong Jin

“…Abstract Images captured from a drone’s perspective are significantly impacted in terms of target detection algorithm performance due to the notable differences in target scales and the presence of numerous small target objects lacking detailed information. …”
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Multi-strategy enhanced marine predator algorithm: performance investigation and application in intrusion detection by Zhongmin Wang, Yujun Zhang, Jun Yu, YuanYuan Gao, Guangwei Zhao, Essam H. Houssein, Rui Zhong

“…Abstract Marine Predator Algorithm (MPA) is a recently proposed population-based metaheuristic algorithm (MA), and its effectiveness has been proven in many stochastic optimization challenges. …”
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Assessing ML classification algorithms and NLP techniques for depression detection: An experimental case study. by Giuliano Lorenzoni, Cristina Tavares, Nathalia Nascimento, Paulo Alencar, Donald Cowan

“…<h4>Conclusions</h4>More comprehensive assessments of ML classification algorithms and NLP techniques for depression detection can advance the state of the art in terms of improved experimental settings and performance.…”
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A Clustering Algorithm Based on the Detection of Density Peaks and the Interaction Degree Between Clusters by Yangming Liu, Jiaman Ding, Hongbin Wang, Yi Du

“…In order to cope with data with an irregular shape and uneven density, this paper proposes a two-phase clustering algorithm based on detecting the peaks of dimensional density and the degree of interaction between clusters (CPDD-ID). …”
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Is the problem of intact coronary arteries still or is it close to solving? by A. N. Sumin

“…The dominant paradigm in the diagnosis of patients with stable coronary artery disease was the identification of patients with obstructive lesions of the coronary arteries, and then - ensuring the possibility of myocardial revascularization. The diagnostic algorithms used until recently led to the fact that in invasive coronary angiography obstructive changes in the coronary arteries were detected in less than half of the cases. …”
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Small target detection algorithm based on SAHI-Improved-YOLOv8 for UAV imagery: A case study of tree pit detection by Xiuhao Liang, Jun Xiang, Sheng Qin, Yundan Xiao, Lifen Chen, Dongxia Zou, Honglun Ma, Dong Huang, Yongxin Huang, Wei Wei

“…The application of deep learning in tree pit detection of unmanned aerial vehicle (UAV) images has problems such as dense distribution, high density, small size, false detections, missed detections, and high localization error. …”
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Enhanced intrusion detection model based on principal component analysis and variable ensemble machine learning algorithm by Ayuba John, Ismail Fauzi Bin Isnin, Syed Hamid Hussain Madni, Farkhana Binti Muchtar

“…Several IDS models have various security problems, such as low detection accuracy and high false alarms, which can be caused by the network traffic dataset's excessive dimensionality and class imbalance in the creation of IDS models. …”
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A New Quotient and Iterative Detection Method in an Affine Krylov Subspace for Solving Eigenvalue Problems by Chein-Shan Liu, Jiang-Ren Chang, Jian-Hung Shen, Yung-Wei Chen

“…For both symmetric and nonsymmetric eigenvalue problems solved by the third algorithm, we develop a simple iterative detection method to maximize the Euclidean norm of the eigenvector in terms of the eigen-parameter, of which the peaks of the response curve correspond to the eigenvalues. …”
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HUMAN EMOTION RECOGNITION SYSTEM USING DEEP LEARNING ALGORITHMS by Kateryna Yuvchenko, Valentyn Yesilevskyi, Olena Sereda

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Malware detection approach based on improved SOINN by Bin ZHANG, Lixun LI, Shuqin DONG

“…To deal with the problems of dynamic update of detection model and high computation costs in malware detection model based on batch learning,a novel malware detection approach is proposed by combing SOINN and supervised classifiers,to reduce computation costs and enable the detection model to update dynamically with the assistance of SOINN′s incremental learning characteristic.Firstly,the improved SOINN was given.According to the whole alignment algorithm,search the adjusted weights of neurons under all input sequences in the learning cycle and then calculate the average value of all adjusted weights as the final result,to avoid SOINN′s stability under different input sequences and representativeness of original data,therefore improve malware detection accuracy.Then a data preprocessing algorithm was proposed based on nonnegative matrix factor and Z-score normalization to transfer the malware behavior feature vector from high dimension and high order to low dimension and low order,to speed up and avoid overfitting and further improve detection accuracy.The results of experiments show that proposed approach supports dynamic updating of detection model and has a significantly higher accuracy of detecting unknown new samples and lower computation costs than tradition methods.…”
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Anomaly-Based Intrusion Detection System in Wireless Sensor Networks Using Machine Learning Algorithms by Belal Al-Fuhaidi, Zainab Farae, Farouk Al-Fahaidy, Gawed Nagi, Abdullatif Ghallab, Abdu Alameri

“…Experimental results show that the proposed model can detect intrusions using different ML algorithms with high accuracy. …”
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A low complexity detection algorithm for large scale multiuser MIMO based on message passing by Qiong WANG, Wei YE, Mingming JI

“…According to the problem of high complexity of base station detection in large scale multiuser multiple input multiple output (MIMO) system,a low complexity multiuser variable node full information Gaussian message passing iterative detection algorithm based on forced convergence (VFI-GMPID-FC) was proposed.Firstly,the traditional Gaussian message passing iterative detection (GMPID) algorithm was improved to obtain VFI-GMPID algorithm,the detection performance of the VFI-GMPID algorithm approximates the minimum mean square error detection (MMSE) algorithm,but the complexity was considerably less than the MMSE algorithm.Then,the VFI-GMPID-FC algorithm was proposed to reduce the complexity of the algorithm and improve the detection efficiency.Finally,the simulation results show that the proposed algorithm can effectively reduce the algorithm complexity while ensuring the detection performance.…”
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Fusion of multi-scale and context for small target detection algorithm of unmanned aerial vehicle rescue by LIU Yuan, ZHAO Jing, JIANG Guoping, XU Fengyu, LU Ningyun

“…Aiming at the problem of insufficient feature information contained in small targets under unmanned aerial vehicle (UAV) images that led to insufficient detection accuracy of the model, a small target detection algorithm for UAV sea rescue images that integrated multi-scale and contextual information was proposed. …”
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