A Review to Enhance Operations in an Airport with a Deep Learning and Computer Vision Approach

被引：0

作者：

Kumaar, R. Arun ^{[1
]}

Malavika, S. ^{[1
]}

Monisha, S. ^{[1
]}

Bharani, B. Sowmiya ^{[2
]}

Devanathan, M. ^{[2
]}

机构：

[1] REVA Univ, Bengaluru, India

[2] REVA Univ, Sch Elect & Commun Engn, Bengaluru, India

来源：

SOFT COMPUTING FOR SECURITY APPLICATIONS, ICSCS 2022 | 2023年 / 1428卷

关键词：

Passenger; CNN; Smart airport; Luggage tracking; Paperless boarding;

D O I：

10.1007/978-981-19-3590-9_12

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Over a decade, the airline activities have seen a gradual increase all over the world. One of the reasons we can claim is the enhancing economy. According to International Civil Aviation Organization (ICAO), Civil Aviation Statistics and ICAO staff estimates that the number of airline travelers has increased from 2.25 billion in 2009 to 4.39 billion in 2019 globally. This increasing number of travelers calls for smart airport operations, and since there is an upsurge in utilization of deep learning and computer vision in recent years, a review has been done on how it can be utilized as for smart operations in airport.

引用

页码：145 / 153

页数：9

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