Perception network and data processing method

A data processing apparatus, wherein the apparatus comprises a memory and a processor, the memory stores code, and the processor is configured to obtain the code, to run operations comprising:

• performing convolution processing on input data, to obtain M target feature maps;
• performing convolution processing on M1 target feature maps in the M target feature maps, to obtain M1 first feature maps, wherein M1 is less than M;
• processing M2 target feature maps in the M target feature maps, to obtain M2 second feature maps, wherein M2 is less than M;
• and
• concatenating the M1 first feature maps and the M2 second feature maps, to obtain a concatenated feature map.

A computer storage medium, wherein the computer storage medium stores one or more instructions, and when the instructions are executed by one or more computers, the one or more computers run operations comprising:

• performing convolution processing on input data, to obtain M target feature maps;
• performing convolution processing on M1 target feature maps in the M target feature maps, to obtain M1 first feature maps, wherein M1 is less than M;
• processing M2 target feature maps in the M target feature maps, to obtain M2 second feature maps, wherein M2 is less than M;
• and
• concatenating the M1 first feature maps and the M2 second feature maps, to obtain a concatenated feature map.