Extended Data Fig. 1: Architecture.
From: Deep learning enables fast and dense single-molecule localization with high accuracy
The DECODE network consists of two stacked U-Nets20 with identical layouts (the three networks depicted on the left share parameters). The frame analysis module extracts informative features from three consecutive frames. These features are integrated by the temporal context module. Both U-Nets have two up- and downsampling stages and 48 filters in the first stage. Each stage consists of three fully convolutional layers with 3 × 3 filters. In each downsampling stage, the resolution is halved, and the number of filters is doubled, vice versa in each upsampling stage. Blue arrows show skip connections. Following the temporal context module three output heads with two convolutional layers each produce the output maps which have the same spatial dimensions as the input frames. The first head predicts the Bernoulli probability map p, the second head the spatial coordinates of the detected emitter Δx, Δy, Δz and its intensity N and the third head the associated uncertainties σx, σy, σz, σN. An optional fourth output head can be used for background prediction.
