Method and apparatus for processing convolution operation on layer in neural network

An apparatus for processing a convolution operation on a layer in a neural network, the apparatus comprising:

• a memory configured to store executable instructions;
• and
• a processor configured to execute the instructions to:
• extract a first target feature vector from a target feature map,
• extract a first weight vector matched with the first target feature vector from a first-type weight element, based on matching relationships for depth-wise convolution operations between target feature vectors of the target feature map and weight vectors of the first-type weight element,
• generate a first intermediate feature vector by performing a multiplication operation between the first target feature vector and the first weight vector,
• generate a first hidden feature vector by accumulating the first intermediate feature vector generated based on the first target feature vector and a second intermediate feature vector generated based on a second target feature vector, and
• generate a first output feature vector of an output feature map based on a point-wise convolution operation between the first hidden feature vector and a second-type weight element.

An electronic device, comprising:

• a memory configured to store executable instructions;
• and
• a processor configured to execute the instructions to:
• extract a first target feature vector from a target feature map,
• extract a first weight vector matched with the first target feature vector from a first-type weight element, based on matching relationships for depth-wise convolution operations between target feature vectors of the target feature map and weight vectors of the first-type weight element,
• generate a first intermediate feature vector by performing a multiplication operation between the first target feature vector and the first weight vector,
• generate a first hidden feature vector by accumulating the first intermediate feature vector generated based on the first target feature vector and a second intermediate feature vector generated based on a second target feature vector, and
• generate a first output feature vector of an output feature map based on a point-wise convolution operation between the first hidden feature vector and a second-type weight element.