2024 · 6 articles
Original Research Pages 1–11
Over the years, emotion recognition has become one of the cornerstones of affective computing, enabling machines to recognize and be responsive to human emotions. The current study will present approaches to accurately classify emotions by exploiting multimodal data, namely audio...
Original Research Pages 12–23
A natural way for humans to connect with computers is through gestures, which have many applications in robotics and gaming. Despite this, problems with latency, precision, and adaptability in handling dynamic movements make real-time implementation difficult. In dynamic settings...
Original Research Pages 24–37
One category-invariant methodology for object identification is zero-shot learning (ZSL), which uses semantic embeddings to categorize unseen categories. The ZSL method is indispensable in fields where data is scarce, including medical diagnosis and navigation. This paper propose...
Original Research Pages 38–51
The rapid growth of healthcare data has come with a surge in demand for privacy-preserving cross-domain analytics, hence the development of Federated Hybrid Multi-Modal Analytics (FH-MMA). This advanced framework safely and efficiently provides deep insights through multi-modal i...
Original Research Pages 52–64
Multimodal interaction (MMI) represented by speech and motion data (SMD) has enormous potential in virtual reality (VR) systems. However, real-time synchronization, context-sensitive interpretation, and effective fusion of heterogeneous data modalities remain open. The study pres...
Original Research Pages 65–78
The increasing reliance on intelligent systems in agriculture and autonomous operations dictates the need for robust context-aware decision support systems (CADSS) to cope with heterogeneous and changing conditions. Conventional systems struggle with heterogeneous data and dynami...
