TY - GEN
T1 - Detection of limit situation in segmentation network via CNN
AU - Song, Junho
AU - Park, Sangkyoo
AU - Lim, Myotaeg
N1 - Publisher Copyright:
© 2020 Institute of Control, Robotics, and Systems - ICROS.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/10/13
Y1 - 2020/10/13
N2 - The ability to detect limit situation is an essential element for ensuring safety in semantic segmentation task in self-driving system. In this paper, we study the detection of limit situations on the results of the image semantic segmentation network, and propose a framework consisting of convolution layers and fully connected layers. The mIoU value is deduced to evaluate a performance of semantic segmentation on the image obtained from the front vertical camera of the actual vehicle. The proposed network shows 90.51% accuracy in Hyundai Motor Group road image dataset for reasoning as a result of verification of the test set.
AB - The ability to detect limit situation is an essential element for ensuring safety in semantic segmentation task in self-driving system. In this paper, we study the detection of limit situations on the results of the image semantic segmentation network, and propose a framework consisting of convolution layers and fully connected layers. The mIoU value is deduced to evaluate a performance of semantic segmentation on the image obtained from the front vertical camera of the actual vehicle. The proposed network shows 90.51% accuracy in Hyundai Motor Group road image dataset for reasoning as a result of verification of the test set.
KW - CNN
KW - Detection of limit situation
KW - Self-driving system
KW - Semantic segmentation
UR - http://www.scopus.com/inward/record.url?scp=85098092488&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85098092488&partnerID=8YFLogxK
U2 - 10.23919/ICCAS50221.2020.9268382
DO - 10.23919/ICCAS50221.2020.9268382
M3 - Conference contribution
AN - SCOPUS:85098092488
T3 - International Conference on Control, Automation and Systems
SP - 892
EP - 894
BT - 2020 20th International Conference on Control, Automation and Systems, ICCAS 2020
PB - IEEE Computer Society
T2 - 20th International Conference on Control, Automation and Systems, ICCAS 2020
Y2 - 13 October 2020 through 16 October 2020
ER -