Research on the lightweight detection method of rail internal damage based on improved YOLOv8 by Xiaochun Wu, Shuzhan Yu

“…This model offers efficient and reliable technical support for detecting and classifying internal rail damage in rail flaw detection tasks. …”
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Real-Time Runway Detection Using Dual-Modal Fusion of Visible and Infrared Data by Lichun Yang, Jianghao Wu, Hongguang Li, Chunlei Liu, Shize Wei

“…This study proposes a salient object detection (SOD) method that integrates visible and infrared sensors for robust airport runway detection in complex environments. …”
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Comparative Analysis of Input Image Characteristics in Convolutional Neural Network-based Signature Detection by M. Adamec, M. Turcanik

“…The utilization of the NxN scalable format for machine code instruction representation results in enhanced accuracy, accelerated training, and a considerable reduction in pixel usage, indicating a promising avenue for optimizing the efficiency of malware detection.…”
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Automated graph-based detection of quantum control schemes: Application to molecular laser cooling by Anna Dawid, Niccoló Bigagli, Daniel W. Savin, Sebastian Will

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YOLOv11-GSF: an optimized deep learning model for strawberry ripeness detection in agriculture by Haoran Ma, Qian Zhao, Runqing Zhang, Chunxu Hao, Wenhui Dong, Xiaoying Zhang, Fuzhong Li, Xiaoqin Xue, Gongqing Sun

“…The challenge of efficiently detecting ripe and unripe strawberries in complex environments like greenhouses, marked by dense clusters of strawberries, frequent occlusions, overlaps, and fluctuating lighting conditions, presents significant hurdles for existing detection methodologies. …”
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Unsupervised Hybrid VAE-Based Anomaly Detection for Vehicle Onboard LiDAR Sensors by Nourhen Sboui, Hakim Ghazzai, Mohamed Hadded, Mourad Elhadef, Gianluca Setti

“…The model strikes a good balance between complexity and efficiency, achieving a 10% accuracy improvement compared to existing models, with an accuracy of 95.1% and an F1-score of 82.6%. …”
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ASAD: A Meta Learning-Based Auto-Selective Approach and Tool for Anomaly Detection by Nadia Rashid, Rashid Mehmood, Fahad Alqurashi, Saad Alqahtany, Juan M. Corchado

“…By automating the selection process, the method aims to reduce the reliance on trial-and-error methods, streamline the anomaly detection workflow, and lead to more robust, adaptable, and efficient anomaly detection systems. …”
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Semantic enhancement and change consistency network for semantic change detection in remote sensing images by Zhenghao Jiang, Biao Wang, Peng Zhang, Yanlan Wu, Zhiyuan Ye, Hui Yang

“…By enhancing the model's ability to extract semantic information from complex land-cover classes, we incorporate multi-scale adaptive modules, leveraging the efficient zero-shot capability of SAM2. …”
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LEAF-YOLO: Lightweight Edge-Real-Time Small Object Detection on Aerial Imagery by Van Quang Nghiem, Huy Hoang Nguyen, Minh Son Hoang

“…Using Lightweight-Efficient Aggregating Fusion along with other blocks and techniques, LEAF-YOLO enhances multiscale feature extraction while reducing complexity, targeting small object detection in dense and varied backgrounds. …”
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Detection Model for Cotton Picker Fire Recognition Based on Lightweight Improved YOLOv11 by Zhai Shi, Fangwei Wu, Changjie Han, Dongdong Song, Yi Wu

“…In addition, the convolutional layers in the original C3k2 block are optimized using partial convolutions to reduce computational redundancy and improve inference efficiency. Furthermore, a visual attention mechanism named CBAM-ECA (Convolutional Block Attention Module-Efficient Channel Attention) is designed to suit the complex working conditions of cotton pickers. …”
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RT-DETR-EVD: An Emergency Vehicle Detection Method Based on Improved RT-DETR by Jun Hu, Jiahao Zheng, Wenwei Wan, Yongqi Zhou, Zhikai Huang

“…The proposed RT-DETR-EVD model achieves a breakthrough balance between accuracy, efficiency, and scene adaptability. Its unique lightweight design enhances detection accuracy while significantly reducing model size and accelerating inference. …”
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Spatial features of CO2 for occupancy detection in a naturally ventilated school building by Qirui Huang, Marc Syndicus, Jérôme Frisch, Christoph van Treeck

“…Accurate occupancy information helps to improve building energy efficiency and occupant comfort. Occupancy detection methods based on CO2 sensors have received attention due to their low cost and low intrusiveness. …”
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A Novel YOLOv10-Based Algorithm for Accurate Steel Surface Defect Detection by Liefa Liao, Chao Song, Shouluan Wu, Jianglong Fu

“…The system uses only 2.67 million parameters, demonstrating efficiency. It excels in identifying complex defects like ’rolled in scale’ and ’inclusion’. …”
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The Role of Sensor Technologies in Estrus Detection in Beef Cattle: A Review of Current Applications by Inga Merkelytė, Artūras Šiukščius, Rasa Nainienė

“…Modern beef cattle reproductive management faces increasing challenges due to the growing global demand for beef. Reproductive efficiency is a critical factor determining the productivity and profitability of beef cattle operations. …”
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Organizational and Methodological Approach to the Description and Standardization of Treatment and Diagnostic Processes in a Multidisciplinary Hospital by A. Y. Perminov, N. S. Fomenko, S. S. Petrikov, F. M. Navzadi

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Hybrid CNN–BiLSTM–DNN Approach for Detecting Cybersecurity Threats in IoT Networks by Bright Agbor Agbor, Bliss Utibe-Abasi Stephen, Philip Asuquo, Uduak Onofiok Luke, Victor Anaga

“…This study addresses the limitations of existing IoT threat detection methods, which often struggle with the dynamic nature of IoT environments and the growing complexity of cyberattacks. …”
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Software Methodology for Data Control and Collection for Autonomous Monitoring Systems with a Large Amount of Generated Information on the Example of Software for a Hydrological Ra... by I. S. Serdiukov, V. I. Veremyev, Van Tuan Nguyen

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Point-Level Fusion and Channel Attention for 3D Object Detection in Autonomous Driving by Juntao Shen, Zheng Fang, Jin Huang

“…PointPillars transforms point cloud data into a two-dimensional pseudo-image and employs a 2D CNN for efficient and precise detection. Nevertheless, this approach encounters two primary challenges: (1) the sparsity and disorganization of raw point clouds hinder the model’s capacity to capture local features, thus impacting detection accuracy; and (2) existing models struggle to detect small objects within complex environments, particularly regarding orientation estimation. …”
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Deciphering the complex molecular architecture of the genetically modified soybean FG72 through paired-end whole genome sequencing by Fan Wang, Shengtao Lu, Wenting Xu, Litao Yang

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EGRN-YOLO: An Enhanced Multi-View Remote Sensing Detection Algorithm for Onshore Wind Turbines Based on YOLOv7 by Renzheng Xue, Haiqiang Xu, Qianlong Wu

“…Wind turbines, as the core components of wind power generation systems, play a crucial role in determining the overall generation efficiency and operational safety. However, the challenges posed by complex backgrounds, significant variations in the scale of wind turbine targets, and arbitrary orientations in unmanned aerial vehicle (UAV) remote sensing images have significantly increased the difficulty of real-time wind turbine detection. …”
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