Barefoot Footprint Detection Algorithm Based on YOLOv8-StarNet by Yujie Shen, Xuemei Jiang, Yabin Zhao, Wenxin Xie

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Lightweight defect detection algorithm of tunnel lining based on knowledge distillation by Anfu Zhu, Jiaxiao Xie, Bin Wang, Heng Guo, Zilong Guo, Jie Wang, Lei Xu, SiXin Zhu, Zhanping Yang

“…Aiming at the problems of complex detection model, poor real-time performance and low accuracy of the current tunnel lining defect detection methods, the study proposes a lightweight defect detection algorithm of tunnel lining based on knowledge distillation. …”
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Research on Fire Smoke Detection Algorithm Based on Improved YOLOv8 by Tianxin Zhang, Fuwei Wang, Weimin Wang, Qihao Zhao, Weijun Ning, Haodong Wu

“…The susceptibility of existing fire detection technologies to background interference frequently results in false alarms, missed detections, and low detection accuracy. …”
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Study on Lightweight Bridge Crack Detection Algorithm Based on YOLO11 by Xuwei Dong, Jiashuo Yuan, Jinpeng Dai

“…Traditional detection methods often suffer from low efficiency and insufficient accuracy. …”
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CTDA: an accurate and efficient cherry tomato detection algorithm in complex environments by Zhi Liang, Caihong Zhang, Zhonglong Lin, Guoqiang Wang, Xiaojuan Li, Xiangjun Zou

“…To ensure accuracy and efficiency in detecting cherry tomatoes in complex environments, the study proposes a precise, realtime, and robust target detection algorithm: the CTDA model, to support robotic harvesting operations in unstructured environments.MethodsThe model, based on YOLOv8, introduces a lightweight downsampling method to restructure the backbone network, incorporating adaptive weights and receptive field spatial characteristics to ensure that low-dimensional small target features are not completely lost. …”
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Statistically Bounding Detection Latency in Low-Duty-Cycled Sensor Networks by Yanmin Zhu

“…This paper studies the fundamental problem of bounding detection delays when the sensor network is low duty cycled. …”
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Low-Illumination Parking Scenario Detection Based on Image Adaptive Enhancement by Xixi Xu, Meiqi Zhang, Hao Tang, Weiye Xu, Bowen Sun, Zhu’an Zheng

“…Aiming at the problem of easily missed and misdetected parking spaces and obstacles in the automatic parking perception task under low-illumination conditions, this paper proposes a low-illumination parking space and obstacle detection algorithm based on image adaptive enhancement. …”
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Enhanced object detection in low-visibility haze conditions with YOLOv9s. by Yang Zhang, Bin Zhou, Xue Zhao, Xiaomeng Song

“…Low-visibility haze environments, marked by their inherent low contrast and high brightness, present a formidable challenge to the precision and robustness of conventional object detection algorithms. …”
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Lightweight YOLO models for object detection based on low-rank decomposition by LIN Delü, LIU Chang, CHEN Qi, ZENG Yang, HE Kun

“…This paper proposed a parameter compression algorithm based on low-rank decomposition for the You Only Look Once (YOLO) series of object detection models, aiming to overcome the limited versatility of current lightweight treatment methods for these models. …”
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Low Complexity Optimized AOR Method for Massive MIMO Signal Detection by Muhammad Nauman Irshad, Muhamamd Muzamil Aslam, Rardchawadee Silapunt

“…To determine these parameters systematically, we incorporate an innovative approach using the Nelder-Mead Simplex optimization algorithm. This heuristic optimization technique allows us to find the optimal acceleration and relaxation parameters, thereby achieving superior detection accuracy with faster convergence for challenging system configurations. …”
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Performance Evaluation of Magnetic Wireless Sensor Networks Algorithm for Traffic Flow Monitoring in Chaotic Cities by Haji Said Fimbombaya, Nerey H. Mvungi, Ndyetabura Y. Hamisi, Hashimu U. Iddi

“…The algorithm extracts traffic flow information from resulting magnetic field distortions sensed by magnetic wireless sensor nodes located on the sides of the road. …”
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Positive Anchor Area Merge Algorithm: A Knowledge Distillation Algorithm for Fruit Detection Tasks Based on Yolov8 by Xiangqun Shi, Xian Zhang, Yifan Su, Xun Zhang

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Improving dependability with low power fault detection model for skinny-hash. by Sonal Arvind Barge, Gerardine Immaculate Mary

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DNFE: Directed network flow entropy for detecting tipping points during biological processes. by Xueqing Peng, Rui Qiao, Peiluan Li, Luonan Chen

“…Numerical simulation results demonstrate that the DNFE algorithm is robust across various noise levels and outperforms existing methods in detecting tipping points. …”
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Fixed/Mobile Collaborative Traffic Flow Detection Study Based on Wireless Charging of UAVs by Hao Wu, Mingbo Niu, Biao Wang, Kai Yan, Yuxuan Li, Hanyu Pang

“…To address this issue, it is essential to obtain precise vehicle data as a reliable reference for managing traffic flow during peak periods. In this paper, we propose an intelligent detection scheme using an improved YOLOv8n target recognition algorithm combined with a ByteTrack multi-target tracking algorithm. …”
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Replica Node Detection Using Enhanced Single Hop Detection with Clonal Selection Algorithm in Mobile Wireless Sensor Networks by L. S. Sindhuja, G. Padmavathi

“…These methods incur control overheads and the detection accuracy is low when the replica is selected as a witness node. …”
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Diagnostic algorithm for the detection of carbapenemases and extended-spectrum β-lactamases in carbapenem-resistant Pseudomonas aeruginosa by Stefano Mancini, Laia Garcia-Verellen, Helena M. B. Seth-Smith, Peter M. Keller, Natalia Kolesnik-Goldmann, Muhammad Ali Syed, Irfan Ullah, Vladimira Hinic, Tim Roloff, Adrian Egli, Oliver Nolte

“…We also included a lateral flow immunoassay (Carba-5, NG-Biotech) for confirmation of MBL production and double disc synergy testing (DDST) to improve ESBL detection. …”
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Anomaly detection algorithm based on fractal characteristics of large-scale network traffic by XU Xiao-dong1, ZHU Shi-rui2, SUN Ya-min1

“…Based on the fractal structure of the large-scale network traffic aggregation, anomalies were analyzed qualitatively and quantitatively from perspective of the global and local scaling exponents.Multi-fractal singular spectrum and Lipschitz regularity distribution were used to analyze the fractal parameters of abnormal flow, trying to identify the relationship between the changes of these parameters and the emergence of anomalies.Experimental results show that the emergence of anomalies has obvious signs on the singular spectrum and Lipschitz regularity distribution.Using this feature, a new multi-fractal-based anomaly detection algorithm and a new detection framework were constructed.On the DARPA/Lincoln laboratory intrusion detection evaluation data set 1999, this algorithm’s detection rate is high at low false alarm rate, which is better than EMERALD.…”
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Machine learning algorithms to detect patient–ventilator asynchrony: a feasibility study by Guillermo Gutierrez, Kendrew Wong, Arun Jose, Jeffrey Williams

“…We explored the feasibility of using machine learning algorithms to replicate the assessment of breathing patterns by experienced clinicians, based on airway flow and pressure signals. …”
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Botnet Detection Using Support Vector Machines with Artificial Fish Swarm Algorithm by Kuan-Cheng Lin, Sih-Yang Chen, Jason C. Hung

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