Abstract: An adversarial image generation method, a computer device, and a computer-readable storage medium are provided. The method includes the following. A reference model classification-equivalent with a target classification model is generated according to the target classification model. A target image is obtained and an original noise for the target image is generated according to the reference model. A first noise and the original noise are input into an adversarial model and a second noise corresponding to the first noise is output when the adversarial model meets a convergence condition, where the second noise enhances an information entropy of the original noise. An enhanced noise image corresponding to the target image is generated according to the second noise and the target image, where a classification accuracy of the enhanced noise image in the target classification model is less than a classification accuracy of the target image in the target classification model.

Abstract: An adversarial image generation method, a computer device, and a computer-readable storage medium are provided. The method includes the following. A reference model classification-equivalent with a target classification model is generated according to the target classification model. A target image is obtained and an original noise for the target image is generated according to the reference model. A first noise and the original noise are input into an adversarial model and a second noise corresponding to the first noise is output when the adversarial model meets a convergence condition, where the second noise enhances an information entropy of the original noise. An enhanced noise image corresponding to the target image is generated according to the second noise and the target image, where a classification accuracy of the enhanced noise image in the target classification model is less than a classification accuracy of the target image in the target classification model.

Abstract: Implementation manners of the present disclosure provide an audio interaction method, apparatus, and system. The method includes: determining a user attribute tag, and grouping users into N groups based on the user attribute tag, N being a positive integer that at least is 2; recording an audio file of a user, and extracting decibel information of the audio file of the user from the recorded audio file of the user; and comparing the extracted decibel information of the audio file of the user with decibel information of a user in another group different from a group the user is in, and presenting a comparison result. In the implementation manners of the present disclosure, interaction between grouped users is achieved in an audio manner, therefore, interactive effect is better, and interactive efficiency is improved.