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  1. 1961

    Vehicle detection in drone aerial views based on lightweight OSD-YOLOv10 by Yang Zhang, Xiaobing Chen, Su Sun, Hongfeng You, Yuanyuan Wang, Jianchu Lin, Jiacheng Wang

    Published 2025-07-01
    “…Abstract To address the challenges of low performance in vehicle image detection from UAV aerial imagery, difficulties in small target feature extraction, and the large parameter size of existing models, we propose the OSD-YOLOv10 algorithm, an enhanced version based on YOLOv10n. …”
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  2. 1962

    Multi-Task Water Quality Colorimetric Detection Method Based on Deep Learning by Shenlan Zhang, Shaojie Wu, Liqiang Chen, Pengxin Guo, Xincheng Jiang, Hongcheng Pan, Yuhong Li

    Published 2024-11-01
    “…Subsequently, to effectively improve detection accuracy while reducing model parameters and computational load, we implemented several improvements to the deep learning algorithm, including the MGFF (Multi-Scale Grouped Feature Fusion) module, the LSKA-SPPF (Large Separable Kernel Attention-Spatial Pyramid Pooling-Fast) module, and the GNDCDH (Group Norm Detail Convolution Detection Head). …”
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  3. 1963

    Enhanced Magnetic Wireless Sensor Network Algorithm for Traffic Flow Monitoring in Low-Speed Congested Traffic by Haji Said Fimbombaya, Nerey H. Mvungi, Ndyetabura Y. Hamisi, Hashimu U. Iddi

    Published 2020-01-01
    “…One of the challenges facing such deployment is the development of effective detection signal-processing algorithm in low-speed congested traffic based on the Earth’s magnetic fields. …”
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    Article
  4. 1964

    FBD-SV-2024: Flying Bird Object Detection Dataset in Surveillance Video by Zi-Wei Sun, Ze-Xi Hua, Heng-Chao Li, Zhi-Peng Qi, Xiang Li, Yan Li, Jin-Chi Zhang

    Published 2025-03-01
    “…These attributes pose challenges that need to be addressed when developing flying bird detection methods for surveillance videos. Finally, advanced (video) object detection algorithms were selected for experimentation on the proposed dataset, and the results demonstrated that this dataset remains challenging for the algorithms above.…”
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    Article
  5. 1965

    PRNet: 3D Object Detection Network-Based on Point-Region Fusion by Yufei Fu, Yuhao Guo, Hui Hu

    Published 2025-03-01
    “…This network employs a fusion module named PRF (Point-Region Fusion), utilizing the K-Nearest Neighbors (KNN) algorithm to find the nearest K points corresponding to point cloud features. …”
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  6. 1966
  7. 1967

    Using multiple drug similarity networks to promote adverse drug event detection by Biswajit Padhi, Ruoqi Liu, Yuedi Yang, Xueqiao Peng, Lang Li, Pengyue Zhang, Ping Zhang

    Published 2024-11-01
    “…While post-market spontaneous reports of ADEs remain a cornerstone of pharmacovigilance, most existing signal detection algorithms rely on substantial accumulated data, limiting their applicability to early ADE detection when reports are scarce. …”
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  8. 1968

    Flexi-YOLO: A lightweight method for road crack detection in complex environments. by Jiexiang Yang, Renjie Tian, Zexing Zhou, Xingyue Tan, Pingyang He

    Published 2025-01-01
    “…Road crack detection is critical to global infrastructure maintenance and public safety, and complex background environments and nonlinear damage crack patterns challenge the need for real-time, efficient, and accurate detection.This paper proposes a lightweight yet robust Flexi-YOLO model based on the YOLOv8 algorithm. …”
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    Article
  9. 1969

    A Fault Detection Framework for Rotating Machinery with a Spectrogram and Convolutional Autoencoder by Hoyeon Lee, Jaehong Yu

    Published 2025-07-01
    “…Finally, we construct the fault detection model by applying the one-class classification algorithm to the latent feature vectors of training signals. …”
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    Article
  10. 1970

    Remote Sensing Image Detection Method Combining Dynamic Convolution and Attention Mechanism by Yunfei Zhang, Ming Chen, Cong Chen

    Published 2025-01-01
    “…Traditional CNN downsampling often leads to the loss of small object details and missed detections. This paper proposes an improved YOLOv8 algorithm, incorporating adaptive feature extraction and multi-scale fusion modules to enhance feature representation, effectively capturing the details of small objects. …”
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  11. 1971

    Intelligent Detection of Underwater Defects in Concrete Dams Based on YOLOv8s-UEC by Chenxi Liang, Yang Zhao, Fei Kang

    Published 2024-09-01
    “…This study proposes a concrete dam underwater apparent defect detection algorithm named YOLOv8s-UEC for intelligent identification of underwater defects. …”
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    Article
  12. 1972
  13. 1973

    An Improved 2D Pose Estimation Algorithm for Extracting Phenotypic Parameters of Tomato Plants in Complex Backgrounds by Yawen Cheng, Ni Ren, Anqi Hu, Lingli Zhou, Chao Qi, Shuo Zhang, Qian Wu

    Published 2024-11-01
    “…However, segmentation-based methods are labor-intensive due to their requirement for extensive annotation during training, while object detection approaches exhibit limitations in capturing intricate structural features. …”
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    Article
  14. 1974
  15. 1975

    Research on Defect Detection in Lightweight Photovoltaic Cells Using YOLOv8-FSD by Chao Chen, Zhuo Chen, Hao Li, Yawen Wang, Guangzhou Lei, Lingling Wu

    Published 2025-01-01
    “…Additionally, the regularized Gaussian distribution distance loss function is used to enhance the detection ability for small target defects. Experimental results show that the YOLOv8-FSD lightweight algorithm improves detection accuracy while significantly reducing the number of parameters and computational requirements compared to the original algorithm. …”
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  16. 1976

    Recognition of Handwritten Persian Two-digit Numerals Using a Novel Hybrid SVM/HMM algorithm by Mahsa Aliakbarzadeh, Farbod Razzazi, Alireza Behrad

    Published 2024-02-01
    “…We employed a 4 scale Gabor filter bank (24, 12, 6 and 3 scales) in 6 directions (0, 30, 60, 90, 120, 150 degrees) for feature extraction. The results showed the digit recognition rate of about 98.75 percent for the proposed algorithm on Persian two-digit numerals, while the recognition rates were 98.58 and 95.93 for separate SVM and HMM engines on isolated characters respectively.…”
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  17. 1977
  18. 1978

    Automated concrete exposed reinforcement and corrosion detection and measurement using coloured illumination by Dow Hamish, Darby Andrew, Perry Marcus, Zhang Feng

    Published 2025-01-01
    “…By imaging concrete surfaces using a blue lighting source, the contrast of red-coloured corrosion and exposed reinforcement is enhanced, particularly in greyscale images used by many defect detection algorithms. An inspection algorithm is proposed to segment these features using blue light images and Otsu thresholding, enabling accurate measurement of corrosion surface area. …”
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    Article
  19. 1979
  20. 1980