UM-YOLOv10: Underwater Object Detection Algorithm for Marine Environment Based on YOLOv10 Model by Rengui Mai, Ji Wang

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YOLOv8-DBW: An Improved YOLOv8-Based Algorithm for Maize Leaf Diseases and Pests Detection by Xiang Gan, Shukun Cao, Jin Wang, Yu Wang, Xu Hou

“…To solve the challenges of low detection accuracy of maize pests and diseases, complex detection models, and difficulty in deployment on mobile or embedded devices, an improved YOLOv8 algorithm was proposed. …”
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Proposing Lane and Obstacle Detection Algorithm Using YOLO to Control Self-Driving Cars on Advanced Networks by Phat Nguyen Huu, Quyen Pham Thi, Phuong Tong Thi Quynh

“…To solve problems such as low detection accuracy of traditional image processing methods and poor real-time performance of methods based on deep learning methods, lane and object detection algorithm barriers for smart traffic are proposed. …”
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A multi-scale small object detection algorithm SMA-YOLO for UAV remote sensing images by Shilong Zhou, Haijin Zhou, Lei Qian

“…In the model’s throat, we design a Bidirectional Multi-Branch Auxiliary Feature Pyramid Network (BIMA-FPN), which integrates high-level semantic information with low-level spatial details, improving small object detection while expanding multi-scale receptive fields. …”
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Coherent Detection of Non-Orthogonal Spectrally Efficient Multicarrier Signals Using a Decision Feedback Algorithm by S. B. Makarov, S. V. Zavjalov, D. C. Nguyen, A. S. Ovsyannikova

“…At the same time, the efficiency of the detection algorithm with decision feedback turns out to be significantly lower than that when using the detection algorithm MLSE.Conclusion. …”
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An efficient algorithm for pedestrian fall detection in various image degradation scenarios based on YOLOv8n by Jianhui Xun, Xuefeng Wang, Xiufang Wang, Xiaoliang Fan, Peishuai Yang, Zhifei Zhang

“…Existing pedestrian fall detection systems often suffer from low accuracy and poor performance under challenging conditions such as rain, snow, nighttime, or camera obstructions. …”
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A study on an efficient citrus Huanglong disease detection algorithm based on three-channel aggregated attention by Yizong Wang, Zhengrong Xiao, Hong Wang, Fei Li, Jiya Tian

“…Background Aiming at the problems of complex and diverse field symptoms of citrus Huanglong disease (HLB), low efficiency and insufficient recognition accuracy of traditional detection methods, this study proposes an efficient detection algorithm based on improved You Only Look Once (YOLO)v8. …”
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Anomaly-Based Intrusion Detection for IoMT Networks: Design, Implementation, Dataset Generation, and ML Algorithms Evaluation by Georgios Zachos, Georgios Mantas, Kyriakos Porfyrakis, Joaquim Manuel Camoes Sobral de Bastos, Jonathan Rodriguez

“…In addition, we evaluated the performance of the deployed AIDS during runtime, and the runtime evaluation results indicate: (i) a strong detection performance for some of the integrated ML algorithms, and (ii) a low computational cost (i.e., less than 1 % cpu usage) of the AIDS for all integrated ML algorithms.…”
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Fast Low Rank and Sparse Decomposition Based on Greedy Bilateral Smoothing for Infrared Small Target Detection by Yan-Shan Zhang, Ze-Yin Li, Dong-Dong Pang, Lu-Yao Wang, Cheng-Jun Wu, Kang Duan, Jun-Ming Gao

“…To address this issue, this study presents a fast and robust low rank and sparse decomposition algorithm for infrared small target detection. …”
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Real-time Detection Algorithm of Expanded Feed Image on the Water Surface Based on Improved YOLOv11 by ZHOU Xiushan, WEN Luting, JIE Baifei, ZHENG Haifeng, WU Qiqi, LI Kene, LIANG Junneng, LI Yijian, WEN Jiayan, JIANG Linyuan

“…This replacement further enhanced the network's ability to extract relevant features and improve detection accuracy. To improve the model's detection of small targets, a P2 layer was introduced. …”
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Simplified LSL-Net Architecture for Unmanned Aerial Vehicle Detection in Real-Time by Francisco David Camacho-Gonzalez, Nestor Andres Garcia-Rojas, José Francisco Martínez-Trinidad, Jesús Ariel Carrasco-Ochoa

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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. …”
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Underwater Low-Frequency Magnetic Field Detection Based on <i>Rao</i>’s Sliding Threshold Method by Yi Li, Jiawei Zhang

“…The results show that the proposed method maintains high detection rates even at extremely low SNRs, achieving about 90% detection probability at −13 dB, significantly outperforming traditional energy detectors (with a threshold of 2 dB). …”
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Rapid and Low-Cost Detection of Thyroid Dysfunction Using Raman Spectroscopy and an Improved Support Vector Machine by Xiangxiang Zheng, Guodong Lv, Guoli Du, Zhengang Zhai, Jiaqing Mo, Xiaoyi Lv

“…This study presents a rapid and low-cost method to detect thyroid dysfunction using serum Raman spectroscopy combined with support vector machine (SVM). …”
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IDS alert clustering algorithm based on chaotic particle swarm optimization by Xiao-bo XU, Qin-qin JIANG, Kang-feng ZHENG, Bin WU, Yi-xian YANG

“…The analysis and experiment show that the al-gorithm can significantly reduce the number of alerts improve its quality, and has a high detection rate and low false detection rate.…”
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A Method of Fatigue Driving State Detection Based on Deep Learning by XIONG Qunfang, LIN Jun, YUE Wei

“…Most of those algorithms have complex structure, low efficiency and weak adaptability in face of driver’s individual behavior habit. …”
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Data leakage detection in machine learning code: transfer learning, active learning, or low-shot prompting? by Nouf Alturayeif, Jameleddine Hassine

“…In this article, we aim to explore ML-based approaches for limited annotated datasets to detect code-level data leakage in ML code. We proposed three approaches, namely, transfer learning, active learning, and low-shot prompting. …”
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SSCD-YOLO: Semi-Supervised Cross-Domain YOLOv8 for Pedestrian Detection in Low-Light Conditions by Fangliang Cao, Kai Yan, Hongliang Chen, Zhen Wang, Yunliang Du, Zekang Zheng, Kefan Li, Baozhu Qi, Mingjia Wang

“…To mitigate the domain differences between infrared and visible light images and address the challenges of data annotation and poor pedestrian detection performance in low-light environments, we propose a semi-supervised cross-domain YOLOv8 pedestrian detection model SSCD-YOLO for low-light environments. …”
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YOLORM: An Advanced Key Point Detection Method for Accurate and Efficient Rotameter Reading in Low Flow Environments by Huang Yong, Xia Xing, Xiao Shengwang

“…Moreover, YOLORM exhibited significant reductions in parameter count and computational cost while maintaining or enhancing detection performance relative to state-of-the-art algorithms. …”
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Performance Analysis of Diabetes Detection Using Machine Learning Classifiers by Hung Huynh, Liu Hui, Ngoc Han Nguyen, Ruixuan Qiao

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