Abstract: Embodiments of the present disclosure provide a method and apparatus for training an image recognition model based on a semantic enhancement, a method and apparatus for recognizing an image, an electronic device, and a computer readable storage medium. The method for training an image recognition model based on a semantic enhancement comprises: extracting, from an inputted first image being unannotated and having no textual description, a first feature representation of the first image; calculating a first loss function based on the first feature representation; extracting, from an inputted second image being unannotated and having an original textual description, a second feature representation of the second image; calculating a second loss function based on the second feature representation, and training an image recognition model based on a fusion of the first loss function and the second loss function.

Abstract: A method and apparatus for identifying a display scene, a method and apparatus for training a model, a device, a storage medium and a computer program product are provided. An implementation of the method may comprise: acquiring a feature vector of a to-be-identified image and acquiring a base library feature vector set; ascertaining, from the base library feature vector set, at least two candidate feature vectors based on a similarity coefficient between the feature vector of the to-be-identified image and each feature vector in the base library feature vector set; performing threshold comparisons on similarity coefficients of the at least two candidate feature vectors, to obtain a target feature vector; and determining a display scene of the to-be-identified image based on a display scene tag corresponding to the target feature vector.