Toward a Cluttered Environment for Learning-Based Multi-Scale Overhead Ground Wire Recognition
文献类型：期刊论文
| 作者 | Chang, Wenkai1,2 ; Yang, Guodong1; Li, En1; Liang, Zize1
|
| 刊名 | NEURAL PROCESSING LETTERS
 |
| 出版日期 | 2018-12-01 |
| 卷号 | 48期号:3页码:1789-1800 |
| 关键词 | Power line recognition Conditional generative adversarial nets Power line inspection Hybrid robot |
| ISSN号 | 1370-4621 |
| DOI | 10.1007/s11063-018-9799-3 |
| 通讯作者 | Chang, Wenkai(changwenkai2013@ia.ac.cn) |
| 英文摘要 | In this paper, we propose a learning-based real-time method to recognize and segment an overhead ground wire (OGW) from an image, which is mainly applied to the multi-scale features in a cluttered environment. The recognition and segmentation are implemented under the framework of conditional generative adversarial nets. The generator is an end-to-end convolutional neural network (CNN) with skip connection. The discriminator is a multi-stage CNN and learns the loss function to train the generator. The OGW is recognized and shown in the downsampling visual saliency map. Thus, the location and existence of OGW are verified, which is crucial for the detection in the cluttered environment with structural lines. Detailed experiments and comparisons are performed on real-world images to demonstrate that the proposed method significantly outperforms the traditional method. Additionally, the optimized network achieves approximately 200fps on a graphics card (GTX970) and 30fps on an embedded platform (Jetson TX1). |
| WOS关键词 | POWER-LINE DETECTION ; MAINTENANCE |
| 资助项目 | National Natural Science Foundation of China[61403374] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000451460500031 |
| 出版者 | SPRINGER |
| 资助机构 | National Natural Science Foundation of China |
| 源URL | [http://ir.ia.ac.cn/handle/173211/25713]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队 |
| 通讯作者 | Chang, Wenkai |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Chang, Wenkai,Yang, Guodong,Li, En,et al. Toward a Cluttered Environment for Learning-Based Multi-Scale Overhead Ground Wire Recognition[J]. NEURAL PROCESSING LETTERS,2018,48(3):1789-1800. |
| APA | Chang, Wenkai,Yang, Guodong,Li, En,&Liang, Zize.(2018).Toward a Cluttered Environment for Learning-Based Multi-Scale Overhead Ground Wire Recognition.NEURAL PROCESSING LETTERS,48(3),1789-1800. |
| MLA | Chang, Wenkai,et al."Toward a Cluttered Environment for Learning-Based Multi-Scale Overhead Ground Wire Recognition".NEURAL PROCESSING LETTERS 48.3(2018):1789-1800. |
入库方式： OAI收割
来源：自动化研究所
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