a simple way is to first concatenate them together and then calculate asimilarity matrix. However, it is very difficult to define appropriate weights for different features and also difficult to leverage their complementary and common information. To address this issue, we first computed ...
As shown in Figure 9, the voxelization of 3D models and their representation using the proposed symbol operator-based method allow for the transformation of 3D models into a series of one-dimensional symbol sequences. The calculation of similarity between two 3D models is then transformed into the...
The deep patient representation [17] is compared with measures, such as principal component analysis (PCA), K-means, Gaussian mixture model (GMM), and independent component analysis (ICA), using only one transformation with respect to the original data (shallow feature learning). DeepPatient signi...