Human motion detection in complex scenarios poses challenges due to occlusions. This
paper presents an integrated approach for accurate human motion detections by combining …

The anchor-free object detection CenterNet has the problems that the utilization rate of
detected object features is low, which is difficult to detect morphological changes and …

Multimodal sensors, including vision sensors and wearable sensors, offer valuable
complementary information for accurate recognition tasks. Nonetheless, the heterogeneity …

Feature selection has demonstrated strong performance in emotion recognition using
intrasubject electroencephalography (EEG) data. However, it faces challenges due to …

While the musical instrument classification task is well-studied, there remains a gap in
identifying non-pitched percussion instruments which have greater overlaps in frequency …

The essence of music is inherently multi-modal–with audio and lyrics going hand in hand.
However, there is very less research done to study the intricacies of the multi-modal nature …

Detecting violent content in video frames is a crucial aspect of violence detection.
Combining visual and audio cues is often the most effective way to identify violent behavior …

Automatic speech recognition (ASR) technology has reached a mature level, and improving
performance in data-scarce scenarios has become a key research focus. In this study, we …

Visual biosignals can be used to analyze human behavioral activities and serve as a
primary resource for Facial Expression Recognition (FER). FER computational systems face …

Post-stroke Dysarthria (PSD) is one of the common sequelae of stroke. PSD can harm
patients' quality of life and, in severe cases, be life-threatening. Most of the existing methods …