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    CSGD-YOLO: A Corn Seed Germination Status Detection Model Based on YOLOv8n by Wenbin Sun, Meihan Xu, Kang Xu, Dongquan Chen, Jianhua Wang, Ranbing Yang, Quanquan Chen, Songmei Yang

    Published 2025-01-01
    “…This study further proposes a new module named C2f-UIB-iAFF based on the faster implementation of cross-stage partial bottleneck with two convolutions (C2f), universal inverted bottleneck (UIB), and iterative attention feature fusion (iAFF) to replace the original C2f in YOLOv8, streamlining model complexity and augmenting the feature fusion prowess of the residual structure. …”
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  3. 83

    High-Accuracy Real-Time Fish Detection Based on Self-Build Dataset and RIRD-YOLOv3 by Wenkai Wang, Bingwei He, Liwei Zhang

    Published 2021-01-01
    “…To overcome the inaccuracy of the You Only Look Once v3 (YOLOv3) algorithm in underwater farming environment, a suitable set of hyperparameters was obtained through multiple sets of experiments. …”
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  4. 84

    Smart Agricultural Pest Detection Using I-YOLOv10-SC: An Improved Object Detection Framework by Wenxia Yuan, Lingfang Lan, Jiayi Xu, Tingting Sun, Xinghua Wang, Qiaomei Wang, Jingnan Hu, Baijuan Wang

    Published 2025-01-01
    “…Aiming at the problems of insufficient detection accuracy and high false detection rates of traditional pest detection models in the face of small targets and incomplete targets, this study proposes an improved target detection network, I-YOLOv10-SC. The network leverages Space-to-Depth Convolution to enhance its capability in detecting small insect targets. …”
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    GS-LinYOLOv10: A drone-based model for real-time construction site safety monitoring by Yang Song, ZhenLin Chen, Hua Yang, Jifei Liao

    Published 2025-05-01
    “…To address these limitations, we propose GS-LinYOLOv10, an improved model based on YOLOv10, specifically designed for drone-based safety monitoring. …”
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  8. 88

    Classifying Sunn Pest Damaged and Healthy Wheat Grains Across Different Species with YOLOV8 and Vision Transformers by Melike Çolak, Özgü Özkan, Ali Berkol, Nergis Pervan Akman, Murat Ardıç, Okan Sezer, Nazife Gözde Ayter Arpacıoğlu, Zekiye Budak Başçiftçi, Murat Olgun

    Published 2024-12-01
    “…First, wheat grains were separated from each other using YOLOv8. Then, the dataset was enriched with different data augmentation techniques, and data-efficient vision transformers were used to classify sunn pest-damaged and healthy grains. …”
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  9. 89

    FE-YOLO: An Efficient Deep Learning Model Based on Feature-Enhanced YOLOv7 for Microalgae Identification and Detection by Gege Ding, Yuhang Shi, Zhenquan Liu, Yanjuan Wang, Zhixuan Yao, Dan Zhou, Xuexiu Zhu, Yiqin Li

    Published 2025-01-01
    “…Herein, a Feature-Enhanced YOLOv7 (FE-YOLO) model for microalgae cell identification and detection is proposed. …”
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  10. 90

    The "Low Slow and Small" UAV target detection and tracking algorithm based on improved YOLOv7 and DeepSort by JIAN Yuhong, YANG Huiyue, WANG Xinggang, RONG Yisheng, ZHU Yukun

    Published 2025-02-01
    “…To improve the accuracy of Low altitude unmanned aerial vehicle(UAV) target detection and tracking, an improved UAV detection algorithm based on YOLOv7 and DeepSort framework is proposed. The CBAM attention mechanism is introduced into the backbone network of YOLOv7 algorithm to improve feature extraction ability. …”
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    Enhancing Intelligent Road Target Monitoring: A Novel BGS-YOLO Approach Based on the YOLOv8 Algorithm by Xingyu Liu, Yuanfeng Chu, Yiheng Hu, Nan Zhao

    Published 2024-01-01
    “…Experiments on the public COCO dataset demonstrate that the BGS-YOLO model significantly outperforms the existing YOLOv8n model. Notably, it shows a 7.3% increase in mean average precision (mAP) and a 2.4% improvement in accuracy. …”
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    A New Multiface Target Detection Algorithm for Students in Class Based on Bayesian Optimized YOLOv3 Model by Dongmei Shi, Hongyu Tang

    Published 2022-01-01
    “…Aiming at the problem of small target missing detection in the YOLOv3 network structure, an improved YOLOv3 algorithm based on Bayesian optimization is proposed. …”
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  17. 97

    Weakly Supervised Real-Time Object Detection Based on Salient Map Extraction and the Improved YOLOv5 Model by Yue Ma, Zhuangzhi Zhi

    Published 2022-01-01
    “…In order to improve the accuracy and processing speed of object detection in weakly supervised learning environment, a weakly supervised real-time object detection method based on saliency map extraction and improved YOLOv5 is proposed. For the case where only image-level annotations are available, class-specific saliency maps are generated from the backpropagation process using a VGG-16-based classification network. …”
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