Abstract
Deep learning can be applied on vehicle image classification diverse purposes such as real-time vehicle recognition, vehicle license plate character recognition, vehicle logo identification, and vehicle color classification. We categorize electric vehicle model images according to electric vehicle types and classify each image using Convolutional Neural Network for electric vehicle parking and charging system. The suggested model can support optimization problem of charging equipment installation and usage by recognizing the electric vehicle type real-time basis at the entrance of parking or charging system and directing each vehicle where to park and charge as each has different charge method and needs different charging equipment. The model is built using transfer learning, that is, we pre-train the network with large dataset compensating the small amount of main dataset and then fine-tune the network with our electric vehicle type dataset. We perform 10-fold experiments and achieve final test accuracy of 77.6%.
Original language | English |
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Title of host publication | ACM International Conference Proceeding Series |
Publisher | Association for Computing Machinery |
Pages | 8-11 |
Number of pages | 4 |
ISBN (Print) | 9781450361033 |
DOIs | |
State | Published - 2019 |
Event | 2nd International Conference on Information Science and System, ICISS 2019 - Tokyo, Japan Duration: 16 Mar 2019 → 19 Mar 2019 |
Publication series
Name | ACM International Conference Proceeding Series |
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Volume | Part F148384 |
Conference
Conference | 2nd International Conference on Information Science and System, ICISS 2019 |
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Country/Territory | Japan |
City | Tokyo |
Period | 16/03/19 → 19/03/19 |
Bibliographical note
Publisher Copyright:© 2019 Association for Computing Machinery.
Keywords
- Convolutional Neural Network
- Electric charging
- Electric vehicle
- Transfer learning
- Vehicle classification