Figure 1: Image of pixel coordinate
FIGURE 1
Figure 1: Image of pixel coordinate
Figure 2: Flow of convolutional processing
Figure 3: Product categories and sample images included in the Fashion-MNIST
Figure 4.1: Relationship between the number of clusters and SSE (16 kernel filters)
Figure 4.2: Relationship between the number of clusters and SSE (32 kernel filters)
Figure 4.3: Relationship between the number of clusters and SSE (64 kernel filters)
Figure 4.4: Relationship between the number of clusters and SSE (128 kernel filters)
Figure 4.5: Relationship between the number of clusters and SSE (256 kernel filters)
Figure 5.1: Relationship between the number of clusters and log-likelihood chi-square (16 kernel filters)
Figure 5.2: Relationship between the number of clusters and log-likelihood chi-square (32 kernel filters)
Figure 5.3: Relationship between the number of clusters and log-likelihood chi-square (64 kernel filters)
Figure 5.4: Relationship between the number of clusters and log-likelihood chi-square (128 kernel filters)
Figure 5.5: Relationship between the number of clusters and log-likelihood chi-square (256 kernel filters)
Figure 6: Average value of feature vector finally extracted using 32 of 2 × 2 kernel filters
Figure 7: Number of clusters vs likelihood ratio chi-square
Tables at a glance
Figures at a glance