Real-Time Object Detection System for Hospital Assets Using YOLOv8 by Andalusia, Friska, Suakanto, Sinung, Hamami, Faqih, Mat Raffei, Anis Farihan, Nuryatno, Edi

“…These results show that YOLOv8 performs well in detecting medical devices. …”
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Corrugation and Squat Classification and Detection with VGG16 and YOLOv5 Neural Network Models by Mohd Yazed, Muhammad Syukri, Mohd Yunus, Mohd Amin, Ahmad Shaubari, Ezak Fadzrin, Abdul Hamid, Nor Aziati, Amzah, Azmale, Md Ali, Zulhelmi

“…This study presents a novel approach utilizing deep learning models, VGG16 and YOLOv5, for detecting and classifying railway track defects, explicitly focusing on corrugation and squat defects. …”
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Road damage detection for autonomous driving vehicles using YOLOv8 and salp swarm algorithm by Nik Ahmad Farihin, Mohd Zulkifli, Zuriani, Mustaffa, Mohd Herwan, Sulaiman

“…The model is then retrained using the hyperparameters identified by SSA. The YOLOv8 models optimized using SSA are compared with the original YOLOv8 and other YOLO versions (YOLOv5, YOLOv9, and YOLOv10), demonstrating a 3.5% improvement in accuracy after hyperparameter optimization in detecting road damage.…”
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Oil palm loose fruit detection using YOLOv4 for an autonomous mobile robot collector by Japar, Ahmed Fareed, Ramli, Hafiz Rashidi, Norsahperi, Nor Mohd Haziq, Wan Hasan, Wan Zuha

“…Refined models (YOLOv4-tiling and YOLOv4-tiny-tiling) are then evaluated. …”
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Real-time personal protective equipment compliance detection using you only look once by Nurhanisah, Aminuddin, Nor Azuana, Ramli, Pratondo, Agus

“…Further analysis comparing the selected models based on the confusion matrix shows that YOLOv8 demonstrates more accurate predictions, while YOLOv5 and YOLOv7 primarily detect background, leading to minimal object detection within the bounding boxes.…”
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Multiple distresses detection for asphalt pavement using improved You Only Look Once algorithm based on convolutional neural network by Dan, Han-Cheng, Yan, Peng, Tan, Jiawei, Zhou, Yinchao, Lu, Bingjie

“…Leveraging the YOLOv7 object detection framework, this study introduces YOLOv7-CSP, a refined algorithm tailored for identifying asphalt pavement distress with enhanced precision. …”
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Crowd-based people detection using deep learning by Chen, Lei

“…Overall, YOLOv5 can effectively detect people in crowded environments and prevent missed detection of hard-to-detect small-scale people. …”
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Vehicle number plate detection and verification using yolo frameworks. by H. Hussein, S. Y. S., M. Ariff, M. H., A. Rahman, M. A.

“…This project concerns the application of two YOLO frameworks (YOLOv3 and YOLOv4) for accurate number plate detection. …”
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Image processing and machine learning techniques for Chagas disease detection and identification by Rada, Lavdie, Azzawi, Inass, Kumar, Preet, Brito-Loeza, Carlos Francisco, Karabağ, Cefa, Reyes-Aldasoro, Constantino C.

“…Advanced deep learning architectures like Faster RCNN, RetinaNet, YOLOv8, and FCOS have been adapted, trained, and compared with each other in terms of the detection accuracy of each image. …”
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Unmanned aerial vehicle (UAV) object detection using YOLO detector by Guo, Huanchen

“…Inspired by experiments conducted in this dissertation and related literature, the baseline of YOLOv8 is modified and the modified version achieves 2% ~ 5% higher accuracy.…”
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Development of a cloud-based road surface quality assessment system by Lim, Ka Quan, Nor Azuana, Ramli

“…This research aims to develop a cloud-based system utilizing the You Only Look Once version 8 (YOLOv8) model for assessing road surface quality. …”
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Detection and Measurement System for Button Mushrooms Using Convolutional Neural Network by Yong, Lio Wei, Ambar, Radzi, Abd Wahab, Mohd Helmy, Abd Jamil, Muhammad Mahadi, Choon, Chew Chang

“…The performance of the YOLOv4 models was evaluated across various iterations ranging from 1000 to 6000 iterations. …”
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Comparison of different deep learning object detection algorithms on fruit drying characterization by Umair, Mohammad Yamin, Norazlianie, Sazali, Kettner, Maurice, Mohd Azraai, Mohd Razman, Weiβ, Robert

“…This study employs three deep learning object detection models: You Only Look Once v5m (YOLOv5m), Single Shot Detector (SSD) MobileNet and EfficientDet. …”
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Development of a learning system for robot control by Tan, Chee Wee

“…This project aims to solve the issue with occlusion by using the capability of the YOLOv5 model in fast and accurate object detection, and Transformer Network (TF) with trajectory predictions which proves to outperform current LSTM. …”
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Handbook of Research on Deep Learning Techniques for Cloud-Based Industrial IoT / by Swarnalatha, P. (Purushotham), 1977-, editor 656271, Prabu, S., 1981-, editor 656272, IGI Global (Online service) 631983

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Adaptation of object detection networks under anomalous conditions by Koh, Rachel

“…This paper proposes combining OOD explanation and object detection model into a pipeline that maximizes efficiency and maintains accuracy across different OOD situations. We use YOLOv7 as the object detection model, which accepts different input sizes with a single set of weights. …”
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Fish classification and deep learning by Zhang, Dawei

“…After pretreatment of dataset and cropping operation based on YOLOv7, high classification accuracies for tank A, B, C, and D with 90.14%, 81.74%, 92.81%, and 80.35% are achieved for this meta framework.…”
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Development of robotic grasping of object detection model by Koh, Aloysius Jun Jie

“…It provides a comprehensive documentation of the process involved in training the YOLOv5 robotic grasping model, starting from the stage of image collection, proceeding to the development of algorithms aimed at identifying feasible grasping points based on the detected data, and culminating in the implementation of the model and algorithms onto an actual robotic arm for simulation.…”
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Automatic identification of vehicles from single view by Lim, Nicholas Shin Cheong

“…An autonomous vehicle detection system will be developed through the process of this project, whereby it incorporates the YOLOv4 CSPDarknet 53 architecture to train on images of objects required for detection. …”
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Deep learning for fabric defect detection by Nangia, Saniya

“…In this study, a modified StackBox ensemble method is implemented. The base models, YOLOv8 and RT-DETR, are fine-tuned on a dataset of patterned fabric defects to find the optimal model configurations. …”
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