Research on Intelligent Vehicle Damage Assessment System Based on Computer Vision. (April 2020)
- Record Type:
- Journal Article
- Title:
- Research on Intelligent Vehicle Damage Assessment System Based on Computer Vision. (April 2020)
- Main Title:
- Research on Intelligent Vehicle Damage Assessment System Based on Computer Vision
- Authors:
- Qianqian, Zhu
Weiming, Guo
Ying, Shen
Zihao, Zhao - Abstract:
- Abstract: At present, under the guidance of the new generation of information technology, the rapid accumulation of data, the continuous improvement of computing power, the continuous optimization of algorithm models, and the rapid rise of multi-scene applications have made profound changes in the development environment of artificial intelligence. In this paper, based on the demand of automobile insurance claims and intelligent transportation, combined with abundant basic data and advanced machine vision algorithm, an intelligent damage determination system of 'Artificial Intelligence + Vehicle Insurance' is constructed. This paper first introduces the functions of the intelligent damage assessment system. Secondly, it discusses the realization path of each functional module in detail, and finally puts forward the vision for the future.
- Is Part Of:
- Journal of physics. Volume 1518(2020)
- Journal:
- Journal of physics
- Issue:
- Volume 1518(2020)
- Issue Display:
- Volume 1518, Issue 1 (2020)
- Year:
- 2020
- Volume:
- 1518
- Issue:
- 1
- Issue Sort Value:
- 2020-1518-0001-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-04
- Subjects:
- Physics -- Congresses
530.5 - Journal URLs:
- http://www.iop.org/EJ/journal/1742-6596 ↗
http://ioppublishing.org/ ↗ - DOI:
- 10.1088/1742-6596/1518/1/012050 ↗
- Languages:
- English
- ISSNs:
- 1742-6588
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5036.223000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25323.xml