Background: Hidden Markov Models (HMMs) have proven very useful in computational biology for such applications as sequence pattern matching, gene-finding, and structure prediction...
An image representation framework based on structured sparse model selection is introduced in this work. The corresponding modeling dictionary is comprised of a family of learned ...
Structured Hidden Markov Models (S-HMM) are a variant of Hierarchical Hidden Markov Models; it provides an abstraction mechanism allowing a high level symbolic description of the k...
The need for a sharable resource that can provide deep anatomical knowledge and support inference for biomedical applications has recently been the driving force in the creation o...
The role of modeling and simulation is receiving much press of late. However, the lack of practice in employing a link between the two is alarming. A static model is used to under...