A MULTI-RIVULET FEATURE SYNTHESIS TACTIC FOR TRAFFIC PREDICTION
Main Article Content
Abstract
In this paper, a system in which density of traffic is measured by comparing captured image with real time traffic information against the image of the empty road as reference image is proposed
Downloads
Download data is not yet available.
Metrics
Metrics Loading ...
Article Details
How to Cite
P. HARSHA, NANDDANAA, B. POOJA, A. SHEETHALA. (2023). A MULTI-RIVULET FEATURE SYNTHESIS TACTIC FOR TRAFFIC PREDICTION. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 14(2), 258–272. https://doi.org/10.17762/turcomat.v14i2.13652
Issue
Section
Research Articles
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
