Patent Document ID: 10083375
Application ID: 15783280
Patent Flag: 1

Claim One:
1. A method for reducing computational load of a CNN where CReLU (Concatenated Rectified Linear Units) is used, the method comprising the steps of: configuring a CNN with learned parameters that performs CReLU activation operation of an activation module and convolution operation of a convolutional layer at the same time, including the steps of: (a) comparing, via a comparator in an operation unit of the CNN, an input value corresponding to each of pixel values of an input image with a predetermined reference value and then outputting a comparison result; (b) outputting, via a selector in the operation unit of the CNN, a specific parameter corresponding to the comparison result among multiple parameters of the convolutional layer; and (c) outputting, via a multiplier in the operation unit of the CNN, a multiplication value calculated by multiplying the specific parameter by the input value, and determining the multiplication value as a result value acquired by applying the convolution operation of the convolutional layer to an output of the activation module; wherein the above method steps of (a) to (c) are expressed in the following formula: CReLU_Conv ⁢ ( x , w 1 , w 2 ) = { w 1 ⁢ x , x < 0 w 2 ⁢ x , x ≥ 0 ⁢ ⁢ where ⁢ ⁢ w 1 = - b ⁢ ⁢ and ⁢ ⁢ w 2 = a where CReLU_Conv is an operation result acquired by applying the convolution operation of the convolutional layer to the output of the activation module; x is the input value; w 1 and w 2 are the parameters of the convolutional layer; a and b are element parameters of the convolutional layer to be used to acquire the w 1 and the w 2 ; and the predetermined reference value is 0.