图 书 馆
多面体的分类器进行目标检测的一个案例研究Polyhedral Classifier for Target Detection A Case Study |
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| 课程网址: | http://videolectures.net/icml08_raykar_pcf/ |
| 主讲教师: | Vikas Raykar |
| 开课单位: | 马里兰大学 |
| 开课时间: | 2008-08-05 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | In this study we introduce a novel algorithm for learning a polyhedron to describe the target class. The proposed approach takes advantage of the limited subclass information made available for the negative samples and jointly optimizes multiple hyperplane classifiers each of which is designed to classify positive samples from a subclass of the negative samples. The flat faces of the polyhedron provides robustness whereas multiple faces contributes to the flexibility required to deal with complex datasets. Apart from improving the prediction accuracy of the system, the proposed polyhedral classifier also provides run-time speedups as a by-product when executed in a cascaded framework in real-time. We introduce the Computer Aided Detection for Colon Cancer as a case study and evaluate the performance of the proposed technique on a real-world Colon dataset both in terms of prediction accuracy and online execution speed. We also compare the proposed technique against some benchmark classifiers. |
| 关 键 词: | 多面体; 框架; 基准分类器 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-05-31：吴雨秋(课程编辑志愿者) |
| 阅读次数: | 62 |