Abstract
Image annotation is always an easy task for humans but a tough task for machines. Inspired by human's thinking mode, there is an assumption that the computer has double systems. Each of the systems can handle the task individually and in parallel. In this paper, we introduce a new hierarchical model for image annotation, based on constructing a novel, hierarchical tree, which consists of exploring the relationships between the labels and the features used, and dividing labels into several hierarchies for efficient and accurate labeling.
Original language | English |
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Title of host publication | 2017 IEEE International Conference on Multimedia and Expo, ICME 2017 |
Publisher | IEEE Computer Society |
Pages | 265-270 |
Number of pages | 6 |
ISBN (Electronic) | 9781509060672 |
DOIs | |
Publication status | Published - 28 Aug 2017 |
Event | 2017 IEEE International Conference on Multimedia and Expo, ICME 2017 - Hong Kong, Hong Kong Duration: 10 Jul 2017 → 14 Jul 2017 |
Conference
Conference | 2017 IEEE International Conference on Multimedia and Expo, ICME 2017 |
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Country/Territory | Hong Kong |
City | Hong Kong |
Period | 10/07/17 → 14/07/17 |
Keywords
- Annotation
- Hierarchical
- Label
- Tree
ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Science Applications