In this paper, we focus on the classification of tweets as sources of potential signals for
adverse drug effects (ADEs) or drug reactions (ADRs). Following the intuition that text and …

This article presents our results for the sixth Affective Behavior Analysis in-the-wild (ABAW)
competition. To improve the trustworthiness of facial analysis, we study the possibility of …

The opaqueness of modern digital advertising, exemplified by platforms such as Meta Ads,
raises concerns regarding their autonomous control over audience targeting, pricing …

Depth estimation is crucial in various computer vision applications, including autonomous
driving, robotics, and virtual and augmented reality. An accurate scene depth map is …

In this paper, we present the results of the HSE-NN team in the 4th competition on Affective
Behavior Analysis in-the-wild (ABAW). The novel multi-task EfficientNet model is trained for …

In this work, we examine the vulnerability of language models to universal adversarial
triggers (UATs). We propose a new white-box approach to the construction of layerwise …

In this paper, the computational complexity of the probabilistic neural network for the
classification of high-dimensional data is improved. At first, the class probability densities are …

Multimedia content, such as advertisements and story videos, exhibit a rich blend of
creativity and multiple modalities. They incorporate elements like text, visuals, audio, and …

Online marketing faces formidable challenges in managing and interpreting immense
volumes of data necessary for competitor analysis, content research, and strategic branding …

This paper is devoted to tracking dynamics of psycho-emotional state based on analysis of
the user's facial video and voice. We propose a novel technology with personalized acoustic …