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
收藏
页码：145 / 153
页数：9
相关论文
共 50 条
  • [41] A Computer Vision-Based Approach for Tick Identification Using Deep Learning Models
    Luo, Chu-Yuan
    Pearson, Patrick
    Xu, Guang
    Rich, Stephen M.
    INSECTS, 2022, 13 (02)
  • [42] Computer vision based deep learning approach for toxic and harmful substances detection in fruits
    Sattar, Abdus
    Ridoy, Asif Mahmud
    Saha, Aloke Kumar
    Babu, Hafiz Md. Hasan
    Huda, Mohammad Nurul
    HELIYON, 2024, 10 (03)
  • [43] Move Over Law Compliance Analysis Utilizing a Deep Learning Computer Vision Approach
    Sekula, Przemyslaw
    Shayesteh, Narjes
    He, Qinglian
    Zahedian, Sara
    Moscoso, Rodrigo
    Cholewa, Michal
    APPLIED SCIENCES-BASEL, 2025, 15 (04):
  • [44] A Comprehensive Review on Deep Learning Assisted Computer Vision Techniques for Smart Greenhouse Agriculture
    Akbar, Jalal Uddin Md
    Kamarulzaman, Syafiq Fauzi
    Muzahid, Abu Jafar Md
    Rahman, Md. Arafatur
    Uddin, Mueen
    IEEE ACCESS, 2024, 12 : 4485 - 4522
  • [45] Computer Vision Aided Study for Melanoma Detection: A Deep Learning Versus Conventional Supervised Learning Approach
    Poorna, S. S.
    Reddy, M. Ravi Kiran
    Akhil, Nukala
    Kamath, Suraj
    Mohan, Lekshmi
    Anuraj, K.
    Pradeep, Haripriya S.
    ADVANCED COMPUTING AND INTELLIGENT ENGINEERING, 2020, 1082 : 75 - 83
  • [46] Evolutionary deep learning for computer vision and image processing
    Al-Sahaf, Harith
    Mesejo, Pablo
    Bi, Ying
    Zhang, Mengjie
    APPLIED SOFT COMPUTING, 2024, 151
  • [47] Deep learning-enabled medical computer vision
    Esteva, Andre
    Chou, Katherine
    Yeung, Serena
    Naik, Nikhil
    Madani, Ali
    Mottaghi, Ali
    Liu, Yun
    Topol, Eric
    Dean, Jeff
    Socher, Richard
    NPJ DIGITAL MEDICINE, 2021, 4 (01)
  • [48] Computer vision with deep learning for ship draft reading
    Wang, Bangping
    Liu, Zhiming
    Wang, Haoran
    OPTICAL ENGINEERING, 2021, 60 (02)
  • [49] Deep Learning vs. Traditional Computer Vision
    O'Mahony, Niall
    Campbell, Sean
    Carvalho, Anderson
    Harapanahalli, Suman
    Hernandez, Gustavo Velasco
    Krpalkova, Lenka
    Riordan, Daniel
    Walsh, Joseph
    ADVANCES IN COMPUTER VISION, CVC, VOL 1, 2020, 943 : 128 - 144
  • [50] Advances in solar forecasting: Computer vision with deep learning
    Paletta, Quentin
    Terren-Serrano, Guillermo
    Nie, Yuhao
    Li, Binghui
    Bieker, Jacob
    Zhang, Wenqi
    Dubus, Laurent
    Dev, Soumyabrata
    Feng, Cong
    ADVANCES IN APPLIED ENERGY, 2023, 11
12345