Research and optimization of a multilevel fire detection framework based on deep learning and classical pattern recognition techniques by Qi Liu, Hong Chen, Da Lin

“…Our objective is to further develop FFDNet into a robust, efficient, and widely applicable tool for flame detection, thereby providing significant technical support for fire prevention and response initiatives.…”
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Rice disease detection method based on multi-scale dynamic feature fusion by Qian Fan, Runhao Chen, Bin Li

“…In order to enhance the accuracy of rice leaf disease detection in complex farmland environments, and facilitate the deployment of the deep learning model onto mobile terminals for rapid real-time inference, this paper introduces a disease detection network titled YOLOv11 Multi-scale Dynamic Feature Fusion for Rice Disease Detection (YOLOv11-MSDFF-RiceD). …”
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G-RCenterNet: Reinforced CenterNet for Robotic Arm Grasp Detection by Jimeng Bai, Guohua Cao

“…First, a channel and spatial attention mechanism is introduced to improve the network’s capability to extract target features, significantly enhancing grasp detection performance in complex backgrounds. Second, an efficient attention module search strategy is proposed to replace traditional fully connected layer structures, which not only increases detection accuracy but also reduces computational overhead. …”
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Detecting eavesdropping nodes in the power Internet of Things based on Kolmogorov-Arnold networks. by Rong Wang, Weibin Jiang, Yanjin Shen, Qiqing Yue, Kan-Lin Hsiung

“…Traditional eavesdropping detection methods struggle to adapt to complex and dynamic attack patterns, necessitating the exploration of more intelligent and efficient anomaly localization approaches. …”
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A parallel algorithm for network traffic anomaly detection based on Isolation Forest by Xiaoling Tao, Yang Peng, Feng Zhao, Peichao Zhao, Yong Wang

“…With the rapid development of large-scale complex networks and proliferation of various social network applications, the amount of network traffic data generated is increasing tremendously, and efficient anomaly detection on those massive network traffic data is crucial to many network applications, such as malware detection, load balancing, network intrusion detection. …”
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Sustainability in pharmaceutical analysis: greenness assessment of HPLC methods for paclitaxel by Ruchita Rajput, Sonal Desai

“…Abstract Sustainability in pharmaceutical analysis is gaining significant attention, driven by global initiatives to reduce environmental impact and enhance operational efficiency. This study evaluates the greenness of HPLC-based methods for paclitaxel quantification using seven assessment tools: NEMI, Complex NEMI, Analytical Eco-Scale, SPMS, ChlorTox, RGBfast, and BAGI. …”
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Improved YOLOv8n Models for Object Detection in Remote Sensing Images by Young-Long Chen, Kai-Chun Hung, Jia-Yun Zhang, Ling-Wei Lin

“…However, applying these models to remote sensing images remains challenging due to complex backgrounds, high object scale variation, and the difficulty of detecting small objects. …”
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SGSNet: a lightweight deep learning model for strawberry growth stage detection by Zhiyu Li, Jianping Wang, Guohong Gao, Yufeng Lei, Chenping Zhao, Yan Wang, Haofan Bai, Yuqing Liu, Xiaojuan Guo, Qian Li

“…However, dense planting patterns and complex environments within greenhouses present challenges for accurately detecting growth stages. …”
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Vehicle detection and classification for traffic management and autonomous systems using YOLOv10 by Anning Ji, Xintao Ma

“…Our approach leverages the advantages of each method to enhance detection accuracy and efficiency, especially in complex traffic scenarios. …”
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Multimodal image fusion for ich detection and classification using parallel Dl models by Sri Sangepu Nagaraju, S. Prince Mary, V. Pavani Chandra, Nandam Gayatri

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Research on foreign object intrusion detection in railway tracks based on MSL-YOLO by Hongxia Niu, Dingchao Feng, Tao Hou

“…This integration improves multi-scale feature representation and model efficiency. In addition, a Lightweight Shared Convolutional Detection Head (LSCD) is employed to replace the original head, reducing complexity while maintaining detection accuracy. …”
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YOLO-HVS: Infrared Small Target Detection Inspired by the Human Visual System by Xiaoge Wang, Yunlong Sheng, Qun Hao, Haiyuan Hou, Suzhen Nie

“…The experimental results demonstrate that the proposed approach exhibits enhanced robustness in detecting targets under severe occlusion and low SNR conditions, while enabling efficient real-time infrared small target detection.…”
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CSF-YOLO: A Lightweight Model for Detecting Grape Leafhopper Damage Levels by Chaoxue Wang, Leyu Wang, Gang Ma, Liang Zhu

“…The model employs FasterNet as the backbone network to enhance computational efficiency and reduce model complexity. It substitutes for the nearest-neighbor upsampling with CARAFE to improve small target detection capabilities. …”
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Detection of weeds in vegetables using image classification neural networks and image processing by Huiping Jin, Kang Han, Kang Han, Hongting Xia, Bo Xu, Xiaojun Jin

“…However, the wide variety of weed types and their complex distribution creates difficulties in rapid and accurate weed detection. …”
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Study of conveyor belt deviation detection based on improved YOLOv8 algorithm by Yunfeng Ni, Haixin Cheng, Ying Hou, Ping Guo

“…Abstract Conveyor belt deviation is a commmon and severe type of fault in belt conveyor systems, often resulting in significant economic losses and potential environment pollution. Traditional detection methods have obvious limitations in fault localization precision and analysis accuracy, unable to meet the demands of efficient and real-time fault detection in complex industrial scenarios. …”
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CIDNet: A Maritime Ship Detection Model Based on ISAR Remote Sensing by Fei Liu, Boyang Liu, Hang Zhou, Song Han, Kunlin Zou, Wenjie Lv, Chang Liu

“…The model is based on the Boundary Box Efficient Transformer (BETR) architecture, which combines super-resolution preprocessing, a deep feature extraction network, a feature fusion technique, and a coordinate maintenance mechanism to improve the detection accuracy and real-time performance of ship targets in complex settings. …”
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An image processing technique for optimizing industrial defect detection using dehazing algorithms. by Xuanyi Zhao, Xiaohan Dou, Gengpei Zhang

“…In recent years, the demand for efficient and accurate defect detection algorithms in industrial production has been increasing. …”
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Enhanced anomaly traffic detection framework using BiGAN and contrastive learning by Haoran Yu, Wenchuan Yang, Baojiang Cui, Runqi Sui, Xuedong Wu

“…However, existing methods face many challenges when processing complex high-dimensional traffic data. Especially in dealing with redundant features, data sparsity and nonlinear features, traditional methods often suffer from high computational complexity and low detection efficiency. …”
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Increase the effectiveness of radar detection systems by adapting to the spatial orientation of the object of observation by S. N. Yarmolik, M. V. Svinarskiy, A. S. Khramenkov, E. V. Zaiko

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Performance Comparison of Random Forest and Decision Tree Algorithms for Anomaly Detection in Networks by Rafiq Fajar Ramadhan, Wahid Miftahul Ashari

“…Despite the small difference in accuracy, Decision Tree demonstrated faster prediction times, making it more efficient for time-sensitive applications. This research concludes that while Random Forest provides higher accuracy for complex datasets, Decision Tree offers a more time-efficient solution with comparable accuracy.…”
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