Contrastive Learning-Based Hyperspectral Image Target Detection Using a Gated Dual-Path Network by Jiake Wu, Rong Liu, Nan Wang

“…Finally, the trained encoder is subsequently employed to extract features from the prior spectrum and test pixels, and the cosine similarity between them serves as the detection metric. …”
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A Lightweight Citrus Ripeness Detection Algorithm Based on Visual Saliency Priors and Improved RT-DETR by Yutong Huang, Xianyao Wang, Xinyao Liu, Liping Cai, Xuefei Feng, Xiaoyan Chen

“…Therefore, LightSal-RTDETR effectively solves the citrus ripeness detection problem in orchard scenes with high complexity, offering an efficient solution for smart agriculture applications.…”
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The data dimensionality reduction and bad data detection in the process of smart grid reconstruction through machine learning. by Bo Yu, Zheng Wang, Shangke Liu, Xiaomin Liu, Ruixin Gou

“…To detect false data injection attacks (FDIAs) in power grid reconstruction and solve the problem of high data dimension and bad abnormal data processing in the power system, thereby achieving safe and stable operation of the power grid system, this study introduces machine learning methods to explore the detection of FDIAs. …”
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Landslide detection with Mask R-CNN using complex background enhancement based on multi-scale samples by Xiaohui Liu, Ling Xu, Jinyu Zhang

“…Using the background enhanced samples, the deep learning model can not only learn differences between landslides and complex backgrounds, but also learn the multi-scale features of landslides better. The proposed method was applied to detect landslides that occurred in Jiuzhaigou County, Sichuan Province. …”
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Hybrid islanding detection method using PMU‐ANN approach for inverter‐based distributed generation systems by Mohammad Abu Sarhan, Szymon Barczentewicz, Tomasz Lerch

“…Abstract An essential component of guaranteeing the stability and safety of electricity distribution networks is islanding detection. In this work, a novel method for islanding detection which combined both phasor measurement units (PMU) and artificial neural network (ANN) is proposed. …”
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Mobile malware detection method using improved GhostNetV2 with image enhancement technique by Yao Du, CaiXia Gao, Xi Chen, MengTian Cui, LiLi Xu, AoJi Ning

“…Abstract In recent years, image-based feature extraction and deep learning classification methods are widely used in the field of malware detection, which helps improve the efficiency of automatic malicious feature extraction and enhances the overall performance of detection models. …”
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Colony-YOLO: A Lightweight Micro-Colony Detection Network Based on Improved YOLOv8n by Meihua Wang, Junhui Luo, Kai Lin, Yuankai Chen, Xinpeng Huang, Jiping Liu, Anbang Wang, Deqin Xiao

“…To overcome the problem of inaccurate small-target detection and high computational consumption in mulberry bacterial blight colony detection task, a mulberry bacterial blight colony dataset (MBCD) consisting of 310 images and 23,524 colonies is presented. …”
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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

“…To improve the localization accuracy for small defects, we add a high-resolution small object detection layer (P2 layer) and integrate the Convolutional Block Attention Module (CBAM) to construct a four-scale feature fusion network. …”
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Semi-Supervised Change Detection with Data Augmentation and Adaptive Thresholding for High-Resolution Remote Sensing Images by Wuxia Zhang, Xinlong Shu, Siyuan Wu, Songtao Ding

“…To address the above problems, we propose a semi-supervised change detection method with data augmentation and adaptive threshold updating (DA-AT) for high-resolution remote sensing images. …”
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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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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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Evaluating Deep Learning Architectures for Breast Tumor Classification and Ultrasound Image Detection Using Transfer Learning by Christopher Kormpos, Fotios Zantalis, Stylianos Katsoulis, Grigorios Koulouras

“…The intersection of medical image classification and deep learning has garnered increasing research interest, particularly in the context of breast tumor detection using ultrasound images. Prior studies have predominantly focused on image classification, segmentation, and feature extraction, often assuming that the input images, whether sourced from healthcare professionals or individuals, are valid and relevant for analysis. …”
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Research on Fault Detection Technology for Circuit Breaker Operating Mechanism Combinations Based on Deep Residual Networks by Hongping Shao, Yizhe Jiang, Jianeng Zhao, Xueteng Li, Mingzhan Zhang, Mingkun Yang, Xinyu Wang, Hao Yang

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Research on Lightweight Open-Pit Mine Driving Obstacle Detection Algorithm Based on Improved YOLOv8s by Bo Xu, Wubin Xu, Bing Li, Hanwen Zhang, Yuanbin Xiao, Weixin Zhou

“…In view of the fact that the current obstacle detection algorithm struggles to strike a balance between high precision and real-time performance, and there are problems such as difficulty in model deployment or unsuitability for practical applications, a lightweight open-pit mine driving obstacle detection algorithm based on improved YOLOv8s is proposed, which is committed to improving the driving safety of unmanned engineering machinery in open-pit mines. …”
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MXT-YOLOv7t: An Efficient Real-Time Object Detection for Autonomous Driving in Mixed Traffic Environments by Afdhal Afdhal, Khairun Saddami, Mirshal Arief, Sugiarto Sugiarto, Zahrul Fuadi, Nasaruddin Nasaruddin

“…This model enhances YOLOv7-tiny P5 by improving the detection rate and reducing inference time. The enhancements include refining the feature extraction network by integrating a lightweight attention mechanism into the ELAN blocks and replacing the activation function in each convolution layer with a sigmoid-weighted linear unit. …”
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An AI explained systematic modular approach for enhanced Electricity Theft Detection for urbanized Smart Grid environment by Muhammad Ammar, Nadeem Javaid, Ali Arishi

“…Subsequently, the data balancing module leverages the localized randomized affine shadow sampling to maintain a balanced data distribution by addressing the class imbalance problem. Finally, the proposed SATBlend in the classification module utilizes AlexNet for feature extraction, ShuffleNet for efficient computation, and a temporal convolutional network for temporal correlation detection to enhance the reliability of advanced ETD systems. …”
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Working mode detection method based on bidirectional LSTM for pipe jacking inertial automatic guidance system by Yutong Zu, Lu Wang, Yuanbiao Hu, Gansheng Yang, Boning He, Zheng Zhou

“…Abstract The pipe-jacking inertial guidance method is a key technology to solve the guidance problems of complex pipe-jacking projects, such as long distances and curves. …”
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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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View on the problem of diabetic nephropathy in children and adolescents with type 1 diabetes: the role of renin-angiotensin-aldosterone system (literature review) (part 2) by K. V. Skobeleva, L. V. Tyrtova, I. L. Nikitina, A. S. Olenev

“…Renin-angiotensin-aldosterone system makes a significant contribution to its development. These features require the creation of new diagnostic techniques for earlier detection of pathology.…”
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A Method for Detecting Amplitude-Phase Joint Characteristic Parameters of Wireless Channel for Generating Key Parameters by Qiongying Tan, Shuanglin Huang, Sanjun Liu

“…In this paper, the amplitude and phase joint feature parameter detection method of wireless channel can not only improve the generation rate of random secret key parameters but also make the eavesdropping party’s eavesdropping error rate closer to 0.5. …”
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