Affective computing (AC), like most other areas of computational research, has benefited
tremendously from advances in deep learning (DL). These advances have opened up new …

Unsupervised indoor localization methods have garnered significant attention for their low
training costs and minimal active participation requirements. A crucial approach in this field …

Content-Based Image Retrieval (CBIR) systems are currently a widely used solution for
image retrieval tasks with various applications. Despite the advances achieved, one of the …

The representation of multimedia content experienced tremendous advances in the last
decades. Mainly supported by deep learning models, impressive results have been …

In recent years, the volume of multimedia data has been rapidly increasing across various
applications. Consequently, classification methods capable of handling scenarios with …

The revolutionary advances in image representation have led to impressive progress in
many image understanding-related tasks, primarily supported by Convolutional Neural …

Binary classification (BC) is a practical task that is ubiquitous in real-world problems, such as
distinguishing healthy and unhealthy objects in biomedical diagnostics and defective and …

The exponential growth of computer networks has intensified the requirement for robust
security measures, rendering penetration testing—an essential practice that assesses …

Multimodal humor recognition has gradually drawn attention in recent years, with memes
serving as a prominent form of multimodal communication on the internet. However, current …

In automated penetration testing (APT), agents are tasked with identifying attack targets and
formulating appropriate action plans within partially-observed network environments. The …