A review of methods for the image automatic annotation
Nowadays, image annotation has attracted extensive attention due to the explosive growth of image data. Large amount of researches on AIA have been proposed, mainly including classification-based methods and probabilistic modeling methods. In this paper, a detailed study on state-of-the-art of image...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Conference or Workshop Item |
| Published: |
2021
|
| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/94333/ http://dx.doi.org/10.1088/1742-6596/1892/1/012002 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Nowadays, image annotation has attracted extensive attention due to the explosive growth of image data. Large amount of researches on AIA have been proposed, mainly including classification-based methods and probabilistic modeling methods. In this paper, a detailed study on state-of-the-art of image annotation was presented devoted to a detailed study of image annotation methods. Differences between manual, semi-automatic and automatic annotation were completely distinguished. The criteria for evaluating annotation systems are also presented in this study. In conclusion, a synthesis of methods of automatic image annotation were shown by presenting the pros and cons of each. This synthesis allowed us to examine our choice for automatic image annotation and the importance of integrating user feedback and a semantic. Finally, we participated in our perspective on the issues and challenges in AIA as well as research tendency in the future. |
|---|