图 书 馆
使用树的集合对图像进行自动注释，以进行多层多标签分类Automatic Annotation of Images using Ensembles of Trees for Hierarchical Multi-label Classification |
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| 课程网址: | http://videolectures.net/solomon_dimitrovski_aai/ |
| 主讲教师: | Ivica Dimitrovski |
| 开课单位: | 约瑟夫·斯特凡学院 |
| 开课时间: | 2010-03-26 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | This research presents a large scale system for detection of visual concepts and annotation of images. The system is composed of two parts: feature extraction and classification/ annotation. The feature extraction part provides global and local descriptions of the images in the form of numerical vectors. Using these numerical descriptions, we train a classifier, a predictive clustering tree (PCT), to produce annotations for unseen images. PCTs are able to handle target concepts that are organized in a hierarchy, i.e., perform hierarchical multi-label classification. To improve the classification performance, we construct ensembles (bags and random forests) of PCTs. We evaluate our system on two different databases: IRMA database which contains medical images and the image database from the ImageCLEF[url] 2010 photo annotation task which contains general images. The extensive experiments conducted on the benchmark databases show that our system has very high predictive performance and can be easily scaled to large amounts of visual concepts and data. In addition, our approach is very general: it can be easily extended with new feature extraction methods, and it can thus be easily applied to other domains, types of images and other classification schemes. Furthermore, it can handle arbitrarily sized hierarchies organized as trees or directed acyclic graphs. |
| 关 键 词: | 视觉概念; 图像标注; 预测聚类树 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-09-26：cwx |
| 阅读次数: | 82 |