Deep CNN-based autonomous system for safety measures in logistics transportation
Deep CNN-based autonomous system for safety measures in logistics transportation
About this item
Full title
Author / Creator
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Journal title
Language
English
Formats
Publication information
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Subjects
More information
Scope and Contents
Contents
The careless activity of drivers in logistics transportation is a primary reason inside the vehicle during road accidents. This research aims to reduce the number of accidents caused by a failure of the driver in logistics transportation by incorporating an autonomous system. We propose a convolutional neural network -based architecture to recogniz...
Alternative Titles
Full title
Deep CNN-based autonomous system for safety measures in logistics transportation
Authors, Artists and Contributors
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Primary Identifiers
Record Identifier
TN_cdi_hal_primary_oai_HAL_hal_03655714v1
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_hal_primary_oai_HAL_hal_03655714v1
Other Identifiers
ISSN
1432-7643
E-ISSN
1433-7479
DOI
10.1007/s00500-021-05949-1
