Knowledge Commons of Institute of Automation,CAS
Joint Semantic Segmentation and Edge Detection for Waterline Extraction | |
Yuhang Chen1,2; Bolin Ni1,2; Gaofeng Meng1,2,3; Baoyin Sha4 | |
2022-05 | |
会议名称 | 6th Asian Conference on Pattern Recognition(ACPR 2021) |
会议日期 | 2021-11 |
会议地点 | 线上参会 |
摘要 | Automatic water gauge reading is very important for cargo weighting in ocean transportation. In this process, accurate waterline extraction is an important yet challenging step. Waterline extraction is subjected to many environmental interference factors, e.g., bad illumi- nation, bad weather conditions, ambiguous contours of water stain, etc. In this paper, we propose a joint multitask based deep model for ac- curate waterline extraction. The proposed model consists of two main branches. One branch is used to extract high-level contextual informa- tion. The other branch rooted in shallow layers is used to extract low-level detail features. The two branches are later coupled with each other to co- supervise the estimation of waterline. Our model works well on various conditions, such as uneven light, serious reections, etc. We also intro- duce a new benchmark dataset for waterline extraction. This dataset consists of 360 pictures extracted from 69 videos collected in several ac- tual ports. Furthermore, su cient experiments show that our model is e ective on the introduced dataset and outperforms the state-of-the-art methods. |
收录类别 | EI |
语种 | 英语 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/48748 |
专题 | 多模态人工智能系统全国重点实验室_先进时空数据分析与学习 |
通讯作者 | Gaofeng Meng |
作者单位 | 1.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences 2.School of Artificial Intelligence, University of Chinese Academy of Sciences 3.Centre for Artificial Intelligence and Robotics, HK Institute of Science Innovation, Chinese Academy of Sciences 4.Coal Science and Technology Research Institute |
第一作者单位 | 模式识别国家重点实验室 |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Yuhang Chen,Bolin Ni,Gaofeng Meng,et al. Joint Semantic Segmentation and Edge Detection for Waterline Extraction[C],2022. |
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 | ||
submission157_update(19231KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论