| CPC G06V 10/806 (2022.01) [G06V 10/40 (2022.01); G06V 10/764 (2022.01); G06V 10/7715 (2022.01); G06V 10/82 (2022.01)] | 18 Claims |

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1. A processor-implemented method, comprising:
receiving an input image;
generating first feature data corresponding to global information of the input image by extracting the first feature data using a first feature extraction layer of a neural network with the input image as input;
generating second feature data corresponding to local information of the input image by extracting the second feature data using a second feature extraction layer of the neural network, the second feature extraction layer being an upper layer of the first feature extraction layer;
generating sequentially merged feature data by merging the first feature data corresponding to the global information and sets of second feature data corresponding to local information of the input image output from a plurality of second feature extraction layers of the neural network; and
classifying an object in the input image based on the sequentially merged feature data.
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