In recent years, the increasing variety of nonlinear activation functions (NAFs) in deep neural
networks (DNNs) has led to higher computational demands. However, hardware …

Physiological signal recognition is crucial in emotion recognition, and recent advancements
in multi-modal fusion have enabled the integration of various physiological signals for …

Evaluating students' learning effectiveness is of great importance for gaining a deeper
understanding of the learning process, accurately diagnosing learning barriers, and …

People who have hearing loss can communicate through sign language. The sign language
will subsequently be converted into text, specifically alphabets. This paper presents the …

Emotion recognition from images plays an important role in various industries, including
healthcare, education and marketing, as well as in human-computer interactions. This paper …

Biometric recognition serves as a crucial method for security authentication. With the
continuous advancement of artificial intelligence technologies, the application of deep …

This study aims to revolutionize early depression detection by utilizing emotion recognition
technology with an accuracy of 77.92%. Through the seamless integration of real-time facial …

Though human communication is crucial, individuals with physical obstacles like deafness
and naivety frequently find it challenging to communicate effectively. Utilizing sign language …

Artificial Intelligence (AI) has brought great convenience and help to human society by
improving efficiency, increasing productivity and reducing cost. As a part of deep learning …

The rapid development of drone technology and deep learning algorithms also expands the
possibilities of environmental monitoring, eg, the search and management of water bodies …