Object Detection with Deep Learning Models

Poonkuntran, S; Balamurugan, B.; Dhanraj, Rajesh Kumar

doi:10.1201/9781003206736

Cited by 2 publications

(2 citation statements)

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“…As stated by Poonkuntran et al [21], data preprocessing involves removing HTML tags and URL tags, renaming the data, and resizing the images. Since a portion of the data was collected online, it contained HTML tags and URLs that needed to be eliminated before training the model.…”

Section: Stage 2: Preparation and Trainingmentioning

confidence: 99%

A Comprehensive Analysis of Real-Time Car Safety Belt Detection Using the YOLOv7 Algorithm

Nkuzo,

Sibiya,

Markus

2023

Algorithms

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Using a safety belt is crucial for preventing severe injuries and fatalities during vehicle accidents. In this paper, we propose a real-time vehicle occupant safety belt detection system based on the YOLOv7 (You Only Look Once version seven) object detection algorithm. The proposed approach aims to automatically detect whether the occupants of a vehicle have buckled their safety belts or not as soon as they are detected within the vehicle. A dataset for this purpose was collected and annotated for validation and testing. By leveraging the efficiency and accuracy of YOLOv7, we achieve near-instantaneous analysis of video streams, making our system suitable for deployment in various surveillance and automotive safety applications. This paper outlines a comprehensive methodology for training the YOLOv7 model using the labelImg tool to annotate the dataset with images showing vehicle occupants. It also discusses the challenges of detecting seat belts and evaluates the system’s performance on a real-world dataset. The evaluation focuses on distinguishing the status of a safety belt between two classes: “buckled” and “unbuckled”. The results demonstrate a high level of accuracy, with a mean average precision (mAP) of 99.6% and an F1 score of 98%, indicating the system’s effectiveness in identifying the safety belt status.

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Section: Stage 2: Preparation and Trainingmentioning

confidence: 99%

A Comprehensive Analysis of Real-Time Car Safety Belt Detection Using the YOLOv7 Algorithm

Nkuzo,

Sibiya,

Markus

2023

Algorithms

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“…With its excellent recognition accuracy and excellent computing speed, Yolo algorithm [3] has been loved and respected by many researchers, and research scholars all over the world are devoted to enhance its operation speed or improve its detection performance. In this paper, we will improve the latest version of the algorithm Network model, combined with today's real-time social environment, to detect whether a pedestrian is wearing a mask as the detection target, by comparing the detection rate and accuracy of the algorithm before and after optimization, comparing the differences before and after optimization, so that it can achieve better results in the detection of small and dense targets.…”

Section: Introductionmentioning

confidence: 99%

Research on Yolo-based target recognition detection

Zhang¹

2023

ACE

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With the development of science and technology, the hotness of target recognition detection has increased year by year in recent years, and the subject has its wide application value in various aspects such as medical, daily life and military. This design on the subject, based on the popular target detection algorithm in recent years - Yolo algorithm, based on the latest Yolov5 algorithm model, the improvement and optimization of the algorithm, combined with the hot topics of current affairs, real-time monitoring of whether the target is wearing a mask, using the dataset provided by Aliyun Tianchi, to conduct experiments. The experimental results are: with Yolov5s base model as the prototype, after optimization and improvement, the fusion rate of target features is improved on the basis of maintaining the original training speed, which effectively improves the accuracy and precision of target recognition.

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Object Detection with Deep Learning Models

Cited by 2 publications

References 0 publications

A Comprehensive Analysis of Real-Time Car Safety Belt Detection Using the YOLOv7 Algorithm

A Comprehensive Analysis of Real-Time Car Safety Belt Detection Using the YOLOv7 Algorithm

Research on Yolo-based target recognition detection

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