A method for learning parameters of a CNN for image recognition is provided to be used for hardware optimization which satisfies KPI. The method includes steps of: a learning device (a) instructing a first transposing layer or a pooling layer to generate an integrated feature map by concatenating pixels, per each ROI, on pooled ROI feature maps; (b) instructing a 1×H1 convolutional layer to generate a first adjusted feature map using a first reshaped feature map, generated by concatenating features in H1 channels of the integrated feature map, and instructing a 1×H2 convolutional layer to generate a second adjusted feature map using a second reshaped feature map, generated by concatenating features in H2 channels of the first adjusted feature map; and (c) instructing a second transposing layer or a classifying layer to divide the second adjusted feature map by each pixel, to thereby generate pixel-wise feature maps.