Abstract: Embodiments of this application disclose an image classification method, a device and a storage medium, and belong to the field of image processing. In this method, a target image is processed by using a current neural network model, to obtain a current classification result. The current neural network model is a neural network model i corresponding to a largest probability in a selection result output by a neural network model a, and the selection result includes probabilities corresponding to p neural network models in m neural network models. A current integration result is determined based on the current classification result, and a category of the target image is determined based on the current integration result.

Abstract: This application discloses a neural network construction method and apparatus, and an image processing method and apparatus in the field of artificial intelligence. The neural network construction method includes: constructing search space based on an application requirement of a target neural network, where the search space includes M elements, the M elements are used to indicate M network structures, each of the M elements includes a quantity of blocks in a stage in a corresponding network structure and a channel quantity of each block, and M is a positive integer (S710); and selecting a target network structure from the M network structures based on a distribution relationship among unevaluated elements in the search space (S720). According to the method, a neural network satisfying a performance requirement can be efficiently constructed.