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Modern developments in the fields of natural language processing (NLP) and computer vision (CV) emphasize the increasing importance of generating images from text descriptions. The presented article analyzes and compares two key methods in this area: generative adversarial network with conditional latent semantic analysis (GAN-CLS) and ultra-long transformer network (XLNet). The main components of GAN-CLS, including the generator, discriminator, and text encoder, are discussed in the context of their functional tasks--generating images from text inputs, assessing the realism of generated images, and converting text descriptions into latent spaces, respectively. A detailed comparative analysis of the performance of GAN-CLS and XLNet, the latter of which is widely used in the organic light-emitting diode (OEL) field, is carried out. The purpose of the study is to determine the effectiveness of each method in different scenarios and then provide valuable recommendations for selecting the best method for generating images from text descriptions, taking into account specific tasks and resources. Ultimately, our paper aims to be a valuable research resource by providing scientific guidance for NLP and CV experts. [ABSTRACT FROM AUTHOR]

This work is devoted to the creation of numerical 3D models for studying 3D topographic effects of homogeneous and inhomogeneous media on the results of 2D inversion. To solve the direct problem, the integral equations method (IEM) was applied to simulate the electric field and calculate the values of apparent resistivity. For the numerical solution of the integral equation, a computational mesh, adapted to the terrain features, was constructed. The calculation of the apparent resistivity of the medium was implemented for a pole-dipole array. Calculations have been performed for a conducting medium with 3D local inhomogeneity and the ground surface topography. The influence of the 3D model with topography, flat ground surface, and immersed inhomogeneity on the results of 2D inversion was estimated. Influencing factors of the 3D model, such as the slope angle of the topography, the resistivity ratio of the inhomogeneity and the host medium, the average size of inhomogeneity and topography, the distance from the inhomogeneity to the measuring line for the medium with and without topography, and the distance between the electrodes of the electrical resistivity tomography (ERT) array, were studied. Based on the research results, recommendations and conclusions that can be useful when conducting geophysical studies by the ERT method are drawn. [ABSTRACT FROM AUTHOR]