Part of Advances in Neural Information Processing Systems 10 (NIPS 1997)
Xubo Song, Yaser Abu-Mostafa, Joseph Sill, Harvey Kasdan
In this paper we propose a technique to incorporate contextual informa(cid:173) tion into object classification. In the real world there are cases where the identity of an object is ambiguous due to the noise in the measurements based on which the classification should be made. It is helpful to re(cid:173) duce the ambiguity by utilizing extra information referred to as context, which in our case is the identities of the accompanying objects. This technique is applied to white blood cell classification. Comparisons are made against "no context" approach, which demonstrates the superior classification performance achieved by using context. In our particular application, it significantly reduces false alarm rate and thus greatly re(cid:173) duces the cost due to expensive clinical tests.
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Incorporating Contextual Information in White Blood Cell Identification