Towards The Future of Crab Farming: The Application Of AI with Yolox And Yolov9 To Detect Crab Larvae by Furqan Zakiyabarsi, Rezty Amalia Aras, Yabes Dwi Nugroho H, Muhammad Muhaimin Nur, Dimas Aditya Alfarizi, Muhammad Ulil Amri

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A Lightweight Anti-Unmanned Aerial Vehicle Detection Method Based on Improved YOLOv11 by Yunlong Gao, Yibing Xin, Huan Yang, Yongjuan Wang

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Petrochemical Equipment Detection by Improved Yolov5 with Multiscale Deep Feature Fusion and Attention Mechanism by Zhenqiang Wei, Shaohua Dong, Xuchu Wang

“…In this paper, a one-stage attention mechanism-enhanced Yolov5 network is proposed to detect typical types of petrochemical equipment in industry scene images. …”
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Enhanced YOLOv10 Framework Featuring DPAM and DALSM for Real-Time Underwater Object Detection by Suthir Sriram, Aburvan P., Arun Kaarthic T. P., Nivethitha Vijayaraj, Thangavel Murugan

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A lightweight wheat ear counting model in UAV images based on improved YOLOv8 by Ruofan Li, Xiaohua Sun, Kun Yang, Zhenxue He, Zhenxue He, Xinxin Wang, Xinxin Wang, Chao Wang, Chao Wang, Bin Wang, Fushun Wang, Fushun Wang, Hongquan Liu, Hongquan Liu

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Improved insulator location and defect detection method based on GhostNet and YOLOv5s networks by Jianjun Huang, Xuhong Huang, Ronghao Kang, Zhihong Chen, Junhan Peng

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Research on refined UAV inspection method of wind/solar power stations based on YOLOv8 by Jieyi Pu, Qifeng Zhang, Wenbo Zhao, Wei Zhang, Zengren Qin, Yumeng Zhang

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A Lightweight Laser Chip Defect Detection Algorithm Based on Improved YOLOv7-Tiny by HU Wei, ZHAO Jumin, LI Dengao

“…In this study, a lightweight laser chip defect detection algorithm based on an improved YOLOv7-Tiny is proposed, aiming at addressing the high computational and parameter demands of deep learning applications in defect detection. …”
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Enhanced YOLOv8 Object Detection Model for Construction Worker Safety Using Image Transformations by Yash Seth, M. Sivagami

“…This paper discusses a methodology of improving the performance of an existing approach of object detection, YOLOv8. The proposed work comprises of improved training of model and detection of helmet in worker images, using Test Time Augmentation (TTA) based approach. …”
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Efficient surface crack segmentation for industrial and civil applications based on an enhanced YOLOv8 model by Zeinab F. Elsharkawy, H. Kasban, Mohammed Y. Abbass

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HAD-YOLO: An Accurate and Effective Weed Detection Model Based on Improved YOLOV5 Network by Long Deng, Zhonghua Miao, Xueguan Zhao, Shuo Yang, Yuanyuan Gao, Changyuan Zhai, Chunjiang Zhao

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Applying YOLOv6 as an ensemble federated learning framework to classify breast cancer pathology images by Chhaya Gupta, Nasib Singh Gill, Preeti Gulia, Noha Alduaiji, J. Shreyas, Piyush Kumar Shukla

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Vehicle Flow Detection and Tracking Based on an Improved YOLOv8n and ByteTrack Framework by Jinjiang Liu, Yonghua Xie, Yu Zhang, Haoming Li

“…To address these issues, this paper proposes a vehicle flow detection and tracking method that integrates an improved YOLOv8n model with the ByteTrack algorithm. In the detection module, we introduce the innovative MSN-YOLO model, which combines the C2f_MLCA module, the Detect_SEAM module, and the NWD loss function to enhance feature fusion and improve cross-scale information processing. …”
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The Application of an Intelligent <i>Agaricus bisporus</i>-Harvesting Device Based on FES-YOLOv5s by Hao Ma, Yulong Ding, Hongwei Cui, Jiangtao Ji, Xin Jin, Tianhang Ding, Jiaoling Wang

“…This device mainly comprised a frame, camera, truss-type robotic arm, flexible manipulator, and control system. The FES-YOLOv5s deep learning target detection model was used to accurately identify and locate <i>Agaricus bisporus</i>. …”
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FH-YOLOv4 with Constrained Aspect Ratio Loss for Video Face Detection and Public Safety by Yue Wang, Liang Hong, Dewen Gu, Pingping Fu

“…In this paper, we first introduce the constrained aspect ratio loss (CARLoss) for better facial boxes regression and incorporate it into the modified FH-YOLOv4, then the IoU Tracker-based video face image deduplication algorithm is proposed on the detection level. …”
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A hybrid human fall detection method based on modified YOLOv8s and AlphaPose by Lei Liu, Yeguo Sun, Yinyin Li, Yihong Liu

“…Abstract To address the challenges of low detection accuracy of small objects and weak applicability of the multi-person fall action recognition applications, we propose a hybrid fall detection method based on modified YOLOv8s and AlphaPose called HFDMIA-Pose. Firstly, we use the modified Yolov8s as object detector. …”
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Evaluating sowing uniformity in hybrid rice using image processing and the OEW-YOLOv8n network by Zehua Li, Zehua Li, Yihui Pan, Xu Ma, Yongjun Lin, Xicheng Wang, Hongwei Li

“…Next, an improved model named OEW-YOLOv8n based on YOLOv8n is proposed to identify the number of seeds in a unit seed grid. …”
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A Lightweight Model for Shine Muscat Grape Detection in Complex Environments Based on the YOLOv8 Architecture by Changlei Tian, Zhanchong Liu, Haosen Chen, Fanglong Dong, Xiaoxiang Liu, Cong Lin

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A Fine-Grained Aircraft Target Recognition Algorithm for Remote Sensing Images Based on YOLOV8 by Xiao-Nan Jiang, Xiang-Qian Niu, Fan-Lu Wu, Yao Fu, He Bao, Yan-Chao Fan, Yu Zhang, Jun-Yan Pei

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Mirror Target YOLO: An Improved YOLOv8 Method With Indirect Vision for Heritage Buildings Fire Detection by Jian Liang, Junsheng Cheng

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