公开(公告)号：US20250139960A1

公开(公告)日：2025-05-01

申请号：US19009930

申请日：2025-01-04

Applicant: Xiangtan University

Inventor： Juan Zou ,  Han Chu ,  Yizhang Xia ,  Li Jia ,  Yuan Liu ,  Zhanglu Hou ,  Qi Deng ,  Chang Liang

IPC: G06V10/82 ,  G06V10/70 ,  G06V10/774 ,  G06V10/776

Abstract: Disclosed in the present invention are an image recognition method and system based on multi-population alternate evolution neural architecture search. The image recognition method includes: acquiring image data and determining a search network according to a target task; constructing a supernet and pre-training the supernet according to preset parameters; dividing a network structure search space into L sub-spaces through an L-layer structure of a neural network, and randomly selecting N candidate sub-networks from the sub-spaces to form L initialized populations; sampling multiple populations from the multiple search sub-spaces for alternate evolution, selecting frontier individuals from a merged populations in a multi-objective environment to generate a next parent population for multi-population alternate evolution; and obtaining an optimal neural network model for image recognition. The method and system realize module diversification at lower search costs, significantly reduce the complexity of the search space, and improve search efficiency.