Name
Abstract | ||
|---|---|---|
Over the past few decades, advanced technologies have increased the number of vehicles, including cars and motorcycles. Because of the large increase of vehicles, the traffic flow becomes more complex and the traffic accidents increase as rapidly. To decrease the number of traffic accidents, a number of studies has been made for how to manage the traffic flow. Especially for motorcycles, in this paper, we propose a method that counts the motorcycles by Convolutional Neural Network (CNN). To reveal the effectiveness of the proposed method, a set of experiments were conducted and the experimental results show the proposed method can bring out a good performance that provides a good support for traffic management systems. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1007/978-3-030-14802-7_16 | INTELLIGENT INFORMATION AND DATABASE SYSTEMS, ACIIDS 2019, PT II |
Keywords | Field | DocType |
Motorcycle counting, Deep learning, Convolutional Neural Network, Traffic management, Video surveillance | Traffic flow,Advanced Traffic Management System,Convolutional neural network,Computer science,Artificial intelligence,Deep learning,Machine learning | Conference |
Volume | ISSN | Citations |
11432 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tzung-pei Hong | 1 | 3768 | 483.06 |
| Yu-Chiao Yang | 2 | 0 | 0.68 |
| Ja-Hwung Su | 3 | 329 | 24.53 |
| Chun-Hao Chen | 4 | 305 | 36.00 |