• Journal of Internet Computing and Services
    ISSN 2287 - 1136(Online) / ISSN 1598 - 0170 (Print)
    http://jics.or.kr/

A Study on Model for Drivable Area Segmentation based on Deep Learning


Hyo-jin Jeon, Soo-sun Cho, Journal of Internet Computing and Services, Vol. 20, No. 5, pp. 105-111, Oct. 2019
10.7472/jksii.2019.20.5.105, Full Text:
Keywords: Drivable area segmentation, segmentation, Deep Learning, DeepLab V3+, Mask R-CNN, BDD Dataset

Abstract

Core technologies that lead the Fourth Industrial Revolution era, such as artificial intelligence, big data, and autonomous driving, are implemented and serviced through the rapid development of computing power and hyper-connected networks based on the Internet of Things. In this paper, we implement two different models for drivable area segmentation in various environment, and propose a better model by comparing the results. The models for drivable area segmentation are using DeepLab V3+ and Mask R-CNN, which have great performances in the field of image segmentation and are used in many studies in autonomous driving technology. For driving information in various environment, we use BDD dataset which provides driving videos and images in various weather conditions and day&night time. The result of two different models shows that Mask R-CNN has higher performance with 68.33% IoU than DeepLab V3+ with 48.97% IoU. In addition, the result of visual inspection of drivable area segmentation on driving image, the accuracy of Mask R-CNN is 83% and DeepLab V3+ is 69%. It indicates Mask R-CNN is more efficient than DeepLab V3+ in drivable area segmentation.


Statistics
Show / Hide Statistics

Statistics (Cumulative Counts from November 1st, 2017)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article
[APA Style]
Hyo-jin Jeon and Soo-sun Cho (2019). A Study on Model for Drivable Area Segmentation based on Deep Learning. Journal of Internet Computing and Services, 20(5), 105-111. DOI: 10.7472/jksii.2019.20.5.105.

[IEEE Style]
H. Jeon and S. Cho, "A Study on Model for Drivable Area Segmentation based on Deep Learning," Journal of Internet Computing and Services, vol. 20, no. 5, pp. 105-111, 2019. DOI: 10.7472/jksii.2019.20.5.105.

[ACM Style]
Hyo-jin Jeon and Soo-sun Cho. 2019. A Study on Model for Drivable Area Segmentation based on Deep Learning. Journal of Internet Computing and Services, 20, 5, (2019), 105-111. DOI: 10.7472/jksii.2019.20.5.105.