.png){kind=icon}
返回
Semi-Supervised Learning Model Based Efficient Image Annotation
.png){kind=icon}
PRE
AI
DOI：10.1109/LSP.2009.2028114.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Automatic image annotation is a promising way to achieve more effective image management and retrieval. However, system performances of the existing state-of-the-art keyword annotation schemes are often not so satisfactory. Therefore, image annotation refinement is crucial to improve the imprecise annotation results. In this paper, a novel approach is developed to automatically annotate image content by a semi-supervised learning model. With perceptual visual characteristics, the candidate annotations of unlabelled images are first obtained based on a progressive model. Then, a transducitive model, random walk with restart algorithm is used to refine these candidate annotations and the top ones are reserved as the final annotations. Experiments conducted on the typical Corel dataset show the effectiveness of the proposed approach.
Keyword:
Automatic image annotation
progressive model
semi-supervised learning model
期刊
IF:
9.6
论文数:
1.1W
被引数:
1.7W
机构
引用论文
Analysis of Imatinib and Sorafenib Binding to p38α Compared with c-Abl and b-Raf Provides Structural Insights for Understanding the Selectivity of Inhibitors Targeting the DFG-Out Form of Protein Kinases.png)
Biochemistry
BiochemistryIF0
PREAI
分享收藏The future of imaging: developing the tools for monitoring response to therapy in oncology: the 2009 Sir James MacKenzie Davidson Memorial lecture影像学的未来: 开发监测肿瘤学治疗反应的工具: 2009詹姆斯·麦肯齐·戴维森爵士纪念讲座
OAAI
OAAI分享收藏Expression of the surface antigen A2B7 in adult and developing honeybee olfactory pathway表面抗原A2B7在成年和发育中的蜜蜂嗅觉途径中的表达
PREAI
分享收藏Relationships and Character Transformation in Pyroloideae (Ericaceae) Based on ITS Sequences, Morphology, and Development基于ITS序列、形态学及发育学的Pyroloideae (Ericaceae)亲缘关系与性状转化研究
PREAI
分享收藏Temporal Artery Versus Bladder Thermometry During Perioperative and Intensive Care Unit MonitoringOAAI
OAAI分享收藏 没有更多内容
没有更多内容