Fig. C.2

Download original image
Architecture of the Tiramisu neural network used for the semantic segmentation task. The encoder (left part of the figure) is a subnetwork that works with an increasingly coarse representation of the data by using transition down blocks that reduce the resolution. The decoder (right part of the model) is a subnetwork that progressively combines low-resolution information coming from transition up blocks and high-resolution information coming from the encoder by skip connections. The bottleneck (dense block at the bottom of the figure) is used to refine the high level of understanding that the model has of the input.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.