Comparative analysis of Ag-Net and U-Net techniques for accuracy in image steganography

The present study analyses the comparison of AG-Net and U-Net-based architectures in the field of image steganography with the intention of improving the accuracy of the results. The Constituents and the Methods involved: Based on the sample size of AG-Net (N=16) and U-Net (N=16), the samples that were gathered are of different types of steganography images. These samples were acquired during the collection process. The image segmentation process has been finished, and the steganography technique was utilised in order to extract the textural information. In order to evaluate the detection of concealed data for both groups, artificial intelligence (AI) and other new technologies, in addition to deep learning methodologies, were utilised. Throughout the process of evaluation, the precision of the parameter was taken into consideration. The results that were obtained from the analysis conducted using SPSS indicate that the level of significance is 0.002 (p