Knowledge Commons of Institute of Automation,CAS
RailNet: An Information aggregation network for rail track segmentation | |
Li, Haoran1,2; Zhang, Qichao1,2; Zhao, Dongbin1,2; Chen, Yaran1,2 | |
2020-07 | |
会议名称 | International Joint Conference on Neural Networks (IJCNN) |
会议日期 | 2020-7-19 |
会议地点 | UK |
摘要 | As the basis of scenes understanding for the track inspection task, track segmentation is challenging due to the various illumination conditions, track crossing, and plant coverage. Since the rail has a strong shape prior, strict rail spacing and special distribution in the image, making full use of the spatial information of the rail features becomes an important factor to improve the accuracy of rail segmentation. In this paper, an information aggregation module is proposed to enhance the spatial relationship between pixels of the rail features. In other words, this module expands the receptive field. Furthermore, we build an information aggregation network based on this module, which is called as RailNet. Finally, the RailNet is evaluated in an open train track dataset. Experimental results show that RailNetcan achieve the best performance so far in the dataset of trains. |
收录类别 | EI |
语种 | 英语 |
七大方向——子方向分类 | 强化与进化学习 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/40314 |
专题 | 多模态人工智能系统全国重点实验室_深度强化学习 |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences 2.University of Chinese Academy of Sciences |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Li, Haoran,Zhang, Qichao,Zhao, Dongbin,et al. RailNet: An Information aggregation network for rail track segmentation[C],2020. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
IJCNN-rails_detectio(2070KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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