Using Sequential Context for Image Analysis
作者： Antonio R.C. Paiva , Elizabeth Jurrus , Tolga Tasdizen
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摘要: This paper proposes the sequential context inference (SCI) algorithm for Markov random field (MRF) image analysis. is designed primarily fast on an MRF model, but its application requires also a specific modeling architecture. The architecture composed of sequence stages, each conditional probability labels, conditioned neighborhood input and output previous stage. By learning model at stage sequentially with regards to true stages learn different models which can cope errors in
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researchgate.net 参考文章(13)
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