Unsupervised SAR Image Change Detection Based on Curvelet Fusion and Local Patch Similarity Information Clustering by Yuhao Huang, Zhihui Xin, Guisheng Liao, Penghui Huang, Guangyu Hou, Rui Zou

“…Then the proposed local patch similarity information clustering algorithm is used to classify the image pixels to output the final change map. …”
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Region and Sample Level Domain Adaptation for Unsupervised Infrared Target Detection in Aerial Remote Sensing Images by Lianmeng Jiao, Haifeng Wei, Quan Pan

“…In this article, we develop a new domain adaptation framework for infrared target detection at both the region level and sample level to tackle the problem of negative transfer. …”
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Research on Underwater Small Target Detection Technology Based on Single-Stage USSTD-YOLOv8n by Weiguo Yi, Jinwei Yang, Lingwei Yan

“…Aiming at the problem of low visibility of underwater environment, which leads to the leakage of small target detection and low accuracy, this paper proposes an improved algorithm USSTD-YOLOv8n (Underwater small-size target detection YOLOv8n) based on YOLOv8n. …”
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Low-Voltage Substation Area Topology Recognition Method Based on AKNN Anomaly Detection and ADPC Clustering by Ziyi SHI, Xiangyang XIA, Jiabin LIU, Yangyang GU, Yulong WANG, Jiayao HONG

“…The similarity of voltage series between users in the low-voltage substation area is measured using dynamic time warping (DTW), and the abnormal relationship between users and transformer is checked and corrected with the AKNN anomaly detection algorithm. After getting the right relationship, the ADPC algorithm is used to identify the phase for users in the substation area. …”
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LGR-Net: A Lightweight Defect Detection Network Aimed at Elevator Guide Rail Pressure Plates by Ruizhen Gao, Meng Chen, Yue Pan, Jiaxin Zhang, Haipeng Zhang, Ziyue Zhao

“…In elevator systems, pressure plates secure guide rails and limit displacement, but defects compromise their performance under stress. Current detection algorithms face challenges in achieving high localization accuracy and computational efficiency when detecting small defects in guide rail pressure plates. …”
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Deep learning and support vector machine-recursive feature elimination-based network intrusion detection model by YE Qing, ZHANG Yannian, WU Hao

“…Moreover, both oversampling and under-sampling techniques were utilized to tackle the unbalance problem of data sample distribution. Three deep learning algorithms were used to build the base learner of the ensemble framework, and deep neural network was used to build the meta-learner, so as to improve the performance of DLRF model to detect network attacks. …”
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SDMSEAF-YOLOv8: a framework to significantly improve the detection performance of unmanned aerial vehicle images by Linxuan Li, Xiaoyu Liu, Xuan Chen, Fengjuan Yin, Bin Chen, Yufeng Wang, Fanbin Meng

“…The conventional non-maximum suppression algorithm is improved, so as to reduce the problem of missed detections under a densely occluded scene by setting the attenuation function to adjust the confidence of the treated box based on the overlap between it and the highest-scoring box. …”
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Traffic Foreground Detection at Complex Urban Intersections Using a Novel Background Dictionary Learning Model by Qianxia Cao, Zhengwu Wang, Kejun Long

“…In this study, a novel background subtraction algorithm based on sparse representation is proposed to detect the traffic foreground at complex intersections to obtain traffic parameters. …”
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An abnormal traffic detection method for chain information management system network based on convolutional neural network by Chao Liu, Chunxiang Liu, Changrong Liu

“…Chain information management system is widely used, providing convenience for the operation and management of enterprises. However, the problem of abnormal network traffic becomes increasingly prominent currently. …”
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Machine Learning-Based Attack Detection and Mitigation with Multi-Controller Placement Optimization over SDN Environment by Binod Sapkota, Arjun Ray, Manish Kumar Yadav, Babu R. Dawadi, Shashidhar R. Joshi

“…The study focuses on the design, implementation, and assessment of the optimal placement of multi-controllers using K-means++ and OPTICS in real topologies and an intrusion detection system (IDS) using the XGBoost classification algorithm to detect and mitigate attacks efficiently with accuracy, precision, and recall of 98.5%, 97.0%, and 97.0%, respectively. …”
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A Coverage-Based Cooperative Detection Method for CDUAV: Insights from Prediction Error Pipeline Modeling by Jiong Li, Xianhai Feng, Yangchao He, Lei Shao

“…Next, we analyze target acquisition scenarios during guidance handover and reformulate the collaborative detection problem as a field-of-view (FOV) coverage optimization task on a two-dimensional detection plane. …”
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3D Pulse Image Detection and Pulse Pattern Recognition Based on Subtle Motion Magnification Technology by Chongyang YAO, Yongxin CHOU, Zhiwei LIANG, Haiping YANG, Jicheng LIU, Dongmei LIN

“…To address the problem of large reconstruction errors in 3D pulse signals caused by excessively small out-of-plane displacement of the contact membrane in the existing traditional Chinese medicine fingertip tactile binocular vision detection technology, this study proposes a 3D pulse image detection method based on subtle motion magnification technology and explores its application in pulse pattern recognition. …”
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Method of joint wavelet thresholding and F-NLM de-noising for high-resolution SAR ship detection by Liang TONG, Dan LIU, Zhongbo PENG, Han ZOU, Lumeng WANG, Chunyu ZHANG

“…Next, a YOLOv7 detection algorithm combined with a bi-directional feature pyramid network (Bi-FPN) is selected to effectively aggregate the multi-scale features and further improve the model's accuracy. …”
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An Intelligent Crow Search Optimization and Bi-GRU for Forest Fire Detection System Using Internet of Things by Syed Abdul Moeed, Bellam Surendra Babu, M. Sreevani, B. V. Devendra Rao, R. Raja Kumar and Gouse Baig Mohammed

“…To address this problem, an IoT-based Artificial Intelligence (AI) technique for forest fire detection has been proposed. …”
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Evaluating Deep Learning Architectures for Breast Tumor Classification and Ultrasound Image Detection Using Transfer Learning by Christopher Kormpos, Fotios Zantalis, Stylianos Katsoulis, Grigorios Koulouras

“…These insights are further anticipated to advance future algorithm development and broaden the potential of the research applicability across diverse fields.…”
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Lightweight coal mine conveyor belt foreign object detection based on improved Yolov8n by Jierui Ling, Zhibo Fu, Xinpeng Yuan

“…Abstract To resolve the drawbacks of slow speed, excessive parameters, and high computational demands associated with deep learning-based conveyor belt foreign object detection methods, a lightweight algorithm for detecting foreign objects on conveyors based on an improved Yolov8n model is proposed. …”
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A novel method for optimizing epilepsy detection features through multi-domain feature fusion and selection by Guanqing Kong, Guanqing Kong, Shuang Ma, Shuang Ma, Wei Zhao, Wei Zhao, Haifeng Wang, Haifeng Wang, Qingxi Fu, Qingxi Fu, Jiuru Wang

“…To extract features strongly correlated with epileptic classification detection, an improved particle swarm optimization (PSO) algorithm and Pearson correlation analysis are combined. …”
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Assessing the Effect of Water on Submerged and Floating Plastic Detection Using Remote Sensing and K-Means Clustering by Lenka Fronkova, Ralph P. Brayne, Joseph W. Ribeiro, Martin Cliffen, Francesco Beccari, James H. W. Arnott

“…Marine and freshwater plastic pollution is a worldwide problem affecting ecosystems and human health. Although remote sensing has been used to map large floating plastic rafts, there are research gaps in detecting submerged plastic due to the limited amount of in situ data. …”
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MSS-YOLO: Multi-Scale Edge-Enhanced Lightweight Network for Personnel Detection and Location in Coal Mines by Wenjuan Yang, Yanqun Wang, Xuhui Zhang, Le Zhu, Tenghui Wang, Yunkai Chi, Jie Jiang

“…Finally, the lightweight Shared Convolutional Detection Head (SCDH) ensures real-time detection under limited computational resources. …”
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End-Edge Collaborative Lightweight Secure Federated Learning for Anomaly Detection of Wireless Industrial Control Systems by Chi Xu, Xinyi Du, Lin Li, Xinchun Li, Haibin Yu

“…With the wide applications of industrial wireless network technologies, the industrial control system (ICS) is evolving from wired and centralized to wireless and distributed, during which eavesdropping and attacking become serious problems. To guarantee the security of wireless and distributed ICS, this article establishes an end-edge collaborative lightweight secure federated learning (LSFL) architecture and proposes an LSFL anomaly detection strategy. …”
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