Improved YOLOv8n based helmet wearing inspection method by Xinying Chen, Zhisheng Jiao, Yuefan Liu

Subjects: “…YOLOv8n…”
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BWFER-YOLOv8: An Enhanced Cascaded Framework for Concealed Object Detection by Khalid Ijaz, Ikramullah Khosa, Ejaz A. Ansari, Syed Farooq Ali, Asif Hussain, Faran Awais Butt

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Underwater Target Detection with High Accuracy and Speed Based on YOLOv10 by Zhengliang Hu, Le Cheng, Shui Yu, Pan Xu, Peng Zhang, Rui Tian, Jingqi Han

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Comparative Analysis of YOLOv8 and HSV Methods for Traffic Density Measurement by Prof. I Gede Pasek Suta Wijaya, Muhamad Nizam Azmi, Ario Yudo Husodo

“…This study addresses the challenge of accurately measuring traffic density by comparing the performance of the YOLOv8 segmentation method with the traditional HSV method. …”
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Proposing Algorithm Using YOLOV4 and VGG-16 for Smart-Education by Phat Nguyen Huu, Khang Doan Xuan

“…In the first step, we use YOLOV4 (Kumar et al. 2020; Canu, 2020) to recognize equations and letters associated with the VGG-16 network (Simonyan and Zisserman, 2015) to classify them. …”
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The DNA Replication Stress Hypothesis of Alzheimer’s Disease by Yuri B. Yurov, Svetlana G. Vorsanova, Ivan Y. Iourov

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Research on YOLOv5 Oracle Recognition Algorithm Based on Multi-Module Fusion by Xinhang Zhang, Zhenhua Ma, Yaru Zhang, Huiying Ru

Subjects: “…YOLOv5…”
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Ship Target Detection Algorithm Based on Improved YOLOv3 for Maritime Image by Dehai Chen, Shiru Sun, Zhijun Lei, Heng Shao, Yuzhao Wang

“…This paper proposed a detection method of ships in water based on improved You Only Look Once version 3 (YOLOv3), which is called Feature Attention, Feature Enhancement YOLOv3 (AE-YOLOv3). …”
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Belt conveyor idler fault detection algorithm based on improved YOLOv5 by Cen Pan, Qing Tao, Hao Pei, Biao Wang, Wei Liu

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YOLOv8-CBAM: a study of sheep head identification in Ujumqin sheep by Qing Qin, Qing Qin, Qing Qin, Xingyu Zhou, Xingyu Zhou, Xingyu Zhou, Jiale Gao, Jiale Gao, Jiale Gao, Zhixin Wang, A. Naer, Long Hai, Suhe Alatan, Haijun Zhang, Zhihong Liu, Zhihong Liu, Zhihong Liu

“…In comparison to YOLOv8n, YOLOv8l, YOLOv8m, YOLOv8s, and YOLOv8x, the YOLOv8-CBAM model enhances average accuracy by 0.5%, 1%, 0.7%, 0.7%, and 1.6%, respectively. …”
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The algorithm for foggy weather target detection based on YOLOv5 in complex scenes by Zhaohui Liu, Wenshuai Hou, Wenjing Chen, Jiaxiu Chang

“…Consequently, this paper introduces the YOLOv5-RCBiW model tailored for vehicular vision perception aimed at enhancing feature extraction and recognition. …”
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Research on Energy Efficiency Management of Forklift Based on Improved YOLOv5 Algorithm by Zhenyu Li, Ke Lu, Yanhui Zhang, Zongwei Li, Jia-Bao Liu

“…In the object detection section, the attention mechanism and the replacement network layer were used to improve the performance of YOLOv5. The experimented results showed that, compared with the original YOLOv5 model, the improved model is lighter in size and faster in detection speed without loss of detection precision, which could also meet the requirements for real-time statistics on the operation efficiency of forklifts.…”
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Lightweight Small Target Detection Algorithm Based on YOLOv8 Network Improvement by Xiaoyi Hao, Ting Li

“…The paper introduces SFD-YOLOv8, a lightweight algorithm based on YOLOv8n, with the aim of enhancing detection performance while maintaining a streamlined architecture. …”
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Gated Channel Attention Mechanism YOLOv3 Network for Small Target Detection by Xi Yang, Jin Shi, Juan Zhang

“…In order to solve the problem of low recognition rate and high missed rate in current target detection task, this paper proposes an improved YOLOv3 algorithm based on a gated channel attention mechanism (GCAM) and adaptive up-sampling module. …”
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DM-YOLO: improved YOLOv9 model for tomato leaf disease detection by Abudukelimu Abulizi, Junxiang Ye, Halidanmu Abudukelimu, Wenqiang Guo

“…Therefore, an improved tomato leaf disease detection method, DM-YOLO, based on the YOLOv9 algorithm, is proposed in this paper. Specifically, firstly, lightweight dynamic up-sampling DySample is incorporated into the feature fusion backbone network to enhance the ability to extract features of small lesions and suppress the interference from the background environment; secondly, the MPDIoU loss function is used to enhance the learning of the details of overlapping lesion margins in order to improve the accuracy of localizing overlapping lesion margins. …”
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Real-Time Vehicle Detection and Air Pollution Estimation Using YOLOv9 by Hari Suparwito, Bernardus Galih Hersa Prakoso, Rosalia Arum Kumalasanti, Agnes Maria Polina

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Side-Scan Sonar Small Objects Detection Based on Improved YOLOv11 by Chang Zou, Siquan Yu, Yankai Yu, Haitao Gu, Xinlin Xu

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Grape Target Detection Method in Orchard Environment Based on Improved YOLOv7 by Fuchun Sun, Qiurong Lv, Yuechao Bian, Renwei He, Dong Lv, Leina Gao, Haorong Wu, Xiaoxiao Li

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A recurrent YOLOv8-based framework for event-based object detection by Diego A. Silva, Kamilya Smagulova, Ahmed Elsheikh, Mohammed E. Fouda, Ahmed M. Eltawil

“…This work explores the integration of event-based cameras with advanced object detection frameworks, introducing Recurrent YOLOv8 (ReYOLOV8), a refined object detection framework that enhances a leading frame-based YOLO detection system with spatiotemporal modeling capabilities by adding recurrency. …”
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OW-YOLO: An Improved YOLOv8s Lightweight Detection Method for Obstructed Walnuts by Haoyu Wang, Lijun Yun, Chenggui Yang, Mingjie Wu, Yansong Wang, Zaiqing Chen

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