Method, device, and computer program product for verifying classification result

Abstract

Embodiments of the present disclosure relate to a method, a device, and a computer program product for verifying a classification result. The method comprises: obtaining a plurality of clusters for training samples by clustering feature representations of the training samples using labels of the training samples; determining, based on the plurality of clusters, a clustering class to which an input image belongs; acquiring a classification result of a classification model for the input image; and verifying the degree of reliability of the classification result for the input image based on the clustering class and the classification result. In this manner, the verification according to embodiments of the present disclosure not only easily combines domain-specific knowledge and improves the detection precision, but also saves computational overhead and storage resources, thus enabling the solution to be deployed in edge devices or Internet of Things devices with limited computational power.