Real-time Lightweight CNN for Detecting Road Object of Various Size

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초록

This paper proposed a novel lightweight convolutional neural network suitable for road object detection which not only for small objects, but for large objects. The proposed network outperformed detection performance of existing convolutional neural networks on KITTI datasets and satisfied real-time processing speed of 10ms on PC and 65ms on NVIDIA TX2. The model is suitable for running in an embedded environment with only 3-million weight parameters.

키워드

road object detectionlightweight CNNvarious object sizesreal-time embedded CNN
제목
Real-time Lightweight CNN for Detecting Road Object of Various Size
저자
Lim, ByeonghakYang, BinKim, Hakil
DOI
10.1109/MIPR.2018.00044
발행일
2018
유형
Proceedings Paper
저널명
IEEE 1ST CONFERENCE ON MULTIMEDIA INFORMATION PROCESSING AND RETRIEVAL (MIPR 2018)
페이지
202 ~ 203