In the rapidly advancing field of multi-modal machine learning (MMML), the convergence of
multiple data modalities has the potential to reshape various applications. This paper …

The aim of this systematic review is to synthesize and analyze interconnected monitoring
devices, interoperable digital avatars, and employee monitoring software. In this research …

We draw on a substantial body of theoretical and empirical research on workplace
collaboration software, synthetic training data, and employee engagement analytics. We …

Deep-SDM is a unified layer framework built on TensorFlow/Keras and written in Python
3.12. The framework aligns with the modular engineering principles for the design and …

Artificial intelligence has many applications in various industries, including agriculture. It can
help overcome challenges by providing efficient solutions, especially in the early stages of …

In this article, we cumulate previous research findings indicating that generative artificial
intelligence and emotional state prediction tools can increase labor productivity and …

Although the applications of artificial intelligence especially deep learning had greatly
improved various aspects of intelligent manufacturing, they still face challenges for wide …

With the rapid development of technologies such as computer science, big data, and
artificial intelligence, the emergence of a vast amount of data has brought developmental …

This study investigates the adoption of artificial intelligence (AI) software in manufacturing
companies in Slovenia, Slovakia and Croatia, and across six production areas. This …

This study proposed a new real-time manufacturing process monitoring method to monitor
and detect process shifts in manufacturing operations. Since real-time production process …