Particles Detection System with CR-39 Based on Deep Learning

Figure 2

Basic schematics of the U-Net architecture. The model input is a raw image and its output is a segmented (masked) image of the neutron tracks. The U-Net consists of a contracting path and an expansive path (encoder-decoder). The contracting path follows the typical architecture of a convolutional network while the expansive path consists of an upsampling of the feature map followed by a 2 × 2 convolution (“upconvolution”) and two 3 × 3 convolutions, each followed by a rectified linear activation function (ReLU).