Authors :
Joel M John; Noel Phillip Issac; Jerin Thomas; Subin Alexander; Syamraj B S
Volume/Issue :
Volume 5 - 2020, Issue 7 - July
Google Scholar :
http://bitly.ws/9nMw
Scribd :
https://bit.ly/32w0m9l
DOI :
10.38124/IJISRT20JUL121
Abstract :
This paper details fully automated vehicle
security system involving vehicle model, make detection,
driver face recognition and parking system guided by a
virtual assistant. The core technology of the system is
built using a sequence of deep Convolutional Neural
Networks (CNNs). This system performs face
recognition of the driver and vehicle model, make
detection and permit access by opening barrier gate.
This allows bigger organizations to control and monitor
vehicle traffic as well as gain user data for security
purpose. For quantitive analysis, we show that our
system outperforms the leading vehicle security system.
Proposed paper project website is also available at
http://www.astound.ga/igns.
Keywords :
Virtual Assistant, Recognition, Authorization, Validation, Vehicle, User interaction.
This paper details fully automated vehicle
security system involving vehicle model, make detection,
driver face recognition and parking system guided by a
virtual assistant. The core technology of the system is
built using a sequence of deep Convolutional Neural
Networks (CNNs). This system performs face
recognition of the driver and vehicle model, make
detection and permit access by opening barrier gate.
This allows bigger organizations to control and monitor
vehicle traffic as well as gain user data for security
purpose. For quantitive analysis, we show that our
system outperforms the leading vehicle security system.
Proposed paper project website is also available at
http://www.astound.ga/igns.
Keywords :
Virtual Assistant, Recognition, Authorization, Validation, Vehicle, User interaction.