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An improved autonomous CNN model is developed to mimic the deformation of soft objects through the CNN activity. The internal elastic forces are incorporated in the CNN model as the local connectivity of cells and the external applied force as the independent current source to model the deformation dynamics.
This paper presents a new methodology for the deformation of soft objects by drawing an analogy between cellular neural network (CNN) and elastic ...
This paper presents a new methodology for the deformation of soft objects by drawing an analogy between cellular neural network (CNN) and elastic.
This paper presents a new methodology to simulate soft object deformation by drawing an analogy between a cellular neural network (CNN) and elastic ...
This paper presents a new methodology for the deformation of soft objects bydrawing an analogy between cellular neural network (CNN) and elasticdeformation. An ...
Mar 8, 2016 · PDF | This paper presents a new methodology for the deformation of soft objects by drawing an analogy between cellular neural network (CNN) ...
Abstract. This paper presents a new methodology for the deformable object modelling by drawing an analogy between cellular neural network (CNN) and elastic.
Abstract—This paper presents a new methodology to simulate soft object deformation by drawing an analogy between a cellular neural network (CNN) and elastic ...
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43 genes support the lungfish-coelacanth grouping related to the closest living relative of tetrapods with the Bayesian method under the coalescence model.
This paper presents a new methodology for thedeformable object modelling by drawing an analogybetween cellular neural network (CNN) and elasticdeformation. The ...