Processing images using deep neural networks

A system comprising:

• a deep neural network configured to process data characterizing an input image to generate an alternative representation of the input image, the deep neural network comprising:
• a plurality of subnetworks arranged in a sequence from lowest to highest, the plurality of subnetworks configured to process the data according to the sequence, the plurality of subnetworks comprising a plurality of module subnetworks, each of the module subnetworks comprising:
• a pass-through convolutional layer configured to process a preceding output representation generated by a preceding subnetwork in the sequence and generate a pass-through output,
• one or more groups of neural network layers configured to process the preceding output representation receive to generate a respective group output for each of the one or more groups, wherein at least one group of the one or more groups of neural network layers includes a 1×1 convolutional layer followed by a 3×3 convolutional layer, and
• a concatenation layer configured to concatenate the pass-through output and the group outputs to generate an output representation for the module subnetwork;
• and
• an output layer configured to process the alternative representation of the input image to generate an output from the input image.

A system comprising:

• a deep neural network configured to process data characterizing an input image to generate an alternative representation of the input image, the deep neural network comprising:
• a plurality of subnetworks arranged in a sequence from lowest to highest, the plurality of subnetworks configured to process the data according to the sequence, the plurality of subnetworks comprising a plurality of module subnetworks, each of the module subnetworks comprising:
• a pass-through convolutional layer configured to process a preceding output representation generated by a preceding subnetwork in the sequence and generate a pass-through output,
• a plurality of groups of neural network layers configured to process the preceding output representation receive to generate a respective group output for each of the one or more groups, wherein a first group of the plurality of groups of neural network layers includes a 1×1 convolutional layer followed by a 3×3 convolutional layer, a second group of the plurality of groups of neural network layers includes a 1×1 convolutional layer followed by a 5×5 convolutional layer, and a third group of the plurality of groups of neural network layers includes a 3×3 max pooling layer followed by a 1×1 convolutional layer,
• a concatenation layer configured to concatenate the pass-through output and the group outputs to generate an output representation for the module subnetwork;
• and
• an output layer configured to process the alternative representation of the input image to generate an output from the input image.