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2020 | OriginalPaper | Chapter

Target Detection Experiment Method and Process Based on YOLOV3

Authors : Mengqiao Wang, Yan Zhuang

Published in: Innovative Computing

Publisher: Springer Singapore

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Abstract

Moving target detection is mostly based on the detection of the underlying video information. This paper discusses the five aspects of target detection concept, YOLOV3 principle introduction, experimental method and process, experimental results and discussion, and YOLOV3 application scenario. Moving target detection is the basis for achieving target recognition tracking. Since the video sequence is composed of a sequence of image frames having a certain continuity in time, the detection of the moving object in the video is performed by extracting the sequence of image frames from the video sequence according to a certain period. We use YOLOV3 for target detection experiments. The first step is to configure the model training environment. The second step is to download and open the YOLOv3 project from Github. In the third step, we use Label Img to label the data. In the fourth step, after the model training is over, we test the trained model.

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Metadata
Title
Target Detection Experiment Method and Process Based on YOLOV3
Authors
Mengqiao Wang
Yan Zhuang
Copyright Year
2020
Publisher
Springer Singapore
DOI
https://doi.org/10.1007/978-981-15-5959-4_71

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