標題: Stop Line Detection and Distance Measurement for Road Intersection based on. Deep Learning Neural Network
作者: Lin, Guan-Ting
Santoso, Patrisia Sherryl
Lin, Che-Tsung
Tsai, Chia-Chi
Guo, Jiun-In
交大名義發表
National Chiao Tung University
公開日期: 1-Jan-2017
摘要: In this paper, we introduce Boost-CNN, a robust stop-line detector that can detect objects (stop line) with competitive tradeoff between speed and accuracy. Boost-CNN consists of an AdaBoost classifier and a CNN. The former is our region proposal generator and it is further combined with the later to be a stop-line detector. In addition, an automatic hard mining method is proposed to reduce the number of false alarm. Our proposed detector achieves 91.5% in accuracy and has 100 FPS performance in test time (performed on NVITAA DIGITS DevBox and Titan X GPU).
URI: http://hdl.handle.net/11536/146965
ISSN: 2309-9402
期刊: 2017 ASIA-PACIFIC SIGNAL AND INFORMATION PROCESSING ASSOCIATION ANNUAL SUMMIT AND CONFERENCE (APSIPA ASC 2017)
起始頁: 692
結束頁: 695
Appears in Collections:Conferences Paper