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A Lightweight Object Detection Network for Real-Time Detection of Driver Handheld Call on Embedded Devices

التفاصيل البيبلوغرافية
العنوان: A Lightweight Object Detection Network for Real-Time Detection of Driver Handheld Call on Embedded Devices
المؤلفون: Zuopeng Zhao, Zhongxin Zhang, Xinzheng Xu, Yi Xu, Hualin Yan, Lan Zhang
المصدر: Computational Intelligence and Neuroscience, Vol 2020 (2020)
بيانات النشر: Hindawi Limited
سنة النشر: 2020
المجموعة: Directory of Open Access Journals: DOAJ Articles
مصطلحات موضوعية: Computer applications to medicine. Medical informatics, R858-859.7, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
الوصف: It is necessary to improve the performance of the object detection algorithm in resource-constrained embedded devices by lightweight improvement. In order to further improve the recognition accuracy of the algorithm for small target objects, this paper integrates 5 × 5 deep detachable convolution kernel on the basis of MobileNetV2-SSDLite model, extracts features of two special convolutional layers in addition to detecting the target, and designs a new lightweight object detection network—Lightweight Microscopic Detection Network (LMS-DN). The network can be implemented on embedded devices such as NVIDIA Jetson TX2. The experimental results show that LMS-DN only needs fewer parameters and calculation costs to obtain higher identification accuracy and stronger anti-interference than other popular object detection models.
نوع الوثيقة: article in journal/newspaper
اللغة: English
تدمد: 1687-5265
1687-5273
Relation: http://dx.doi.org/10.1155/2020/6616584; https://doaj.org/toc/1687-5265; https://doaj.org/toc/1687-5273; https://doaj.org/article/b582df98209d44569ff8e8da12d39978
DOI: 10.1155/2020/6616584
الاتاحة: https://doi.org/10.1155/2020/6616584
https://doaj.org/article/b582df98209d44569ff8e8da12d39978
رقم الانضمام: edsbas.AABED648
قاعدة البيانات: BASE
الوصف
تدمد:16875265
16875273
DOI:10.1155/2020/6616584