Hidden Markov models (HMMs) provide a powerful framework for inferring unobserved processes that evolve over time or space by linking an underlying Markovian state sequence to observed data via ...
Recently, several convolutional neural networks have been proposed not only for 2D images, but also for 3D and 4D volume segmentation. Nevertheless, due to the large data size of the latter, acquiring ...
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