发明名称 |
INCORPORATING SPATIAL KNOWLEDGE FOR CLASSIFICATION |
摘要 |
We propose using different classifiers based on the spatial location of the object. The intuitive idea behind this approach is that several classifiers may learn local concepts better than a "universal" classifier that covers the whole feature space. The use of local classifiers ensures that the objects of a particular class have a higher degree of resemblance within that particular class. The use of local classifiers also results in memory, storage and performance improvements, especially when the classifier is kernel-based. As used herein, the term "kernel-based classifier" refers to a classifier where a mapping function (i.e., the kernel) has been used to map the original training data to a higher dimensional space where the classification task may be easier. |
申请公布号 |
WO2005017815(A2) |
申请公布日期 |
2005.02.24 |
申请号 |
WO2004US26425 |
申请日期 |
2004.08.13 |
申请人 |
SIEMENS MEDICAL SOLUTIONS USA, INC. |
发明人 |
KRISHNAN, ARUN;FUNG, GLENN;STOECKEL, JONATHAN |
分类号 |
G06F19/00;G06K9/00;G06K9/62;G06K9/68;G06T7/00 |
主分类号 |
G06F19/00 |
代理机构 |
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代理人 |
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主权项 |
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地址 |
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