Original paper
Auto-context modeling using multiple Kernel learning
Published: Sep 1, 2016
Abstract
In complex visual recognition systems, feature fusion has become crucial to discriminate between a large number of classes. In particular, fusing high-level context information with image appearance models can be effective in object/scene recognition. To this end, we develop an auto-context modeling approach under the RKHS (Reproducing Kernel Hilbert Space) setting, wherein a series of supervised learners are used to approximate the context...
Paper Details
Title
Auto-context modeling using multiple Kernel learning
Published Date
Sep 1, 2016
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