交通场景图像中行人的自动检测

2020 Wave Electronics and its Application in Information and Telecommunication Systems (WECONF) Pub Date : 2020-06-01 DOI:10.1109/WECONF48837.2020.9131458

M. A. Mikhalkova, V. Yachnaya, E. Yablokov, V. Lutsiv

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引用次数: 1

摘要

本文主要研究了基于深度神经网络的行人自动检测。为了实现这一目标，深度神经网络模型DeepLabv3+被用于道路交通场景的分割任务。通过应用训练迁移然后进行微调来减少训练集的可能性是主要的兴趣。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Automatic Detection of Pedestrians in Traffic Scene Images

This article is devoted to automatic detection of pedestrians using a deep neural network. To achieve this goal, the deep neural network model DeepLabv3+ was adapted to the task of segmenting the road traffic scenes. The possibility of reduction of training sets by means of application of training transfer followed by fine tuning was of the primary interest.

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来源期刊

2020 Wave Electronics and its Application in Information and Telecommunication Systems (WECONF)

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