Brain strokes are considered a worldwide medical emergency. In this paper, we present a
new feature extractor that can classify brain computed tomography (CT) scan images into …

In real-life situations where human care robots are deployed, there are custom sound events
whose acoustic characteristics change depending on the user's choice unlike general sound …

Models based on diverse attention mechanisms have recently shined in tasks related to
acoustic event classification (AEC). Among them, self-attention is often used in audio-only …

The sound-detection method of trunk borer is a very promising method in the field of forestry
prevention and control of trunk borers. However, the detection accuracy of commonly used …

Spatial-temporal local binary pattern (STLBP) has been widely used in dynamic texture
recognition. STLBP often encounters the high-dimension problem as its dimension …

In acoustic event recognition (AER), it is important to extract semantic features. As two
crucial aspects of semantic features, the essential content and the temporal structure can …

The challenges of polyphonic sound event detection (PSED) stem from the detection of
multiple overlapping events in a time series. Recent efforts exploit Deep Neural Networks …

Spatial-Temporal Local Binary Pattern (STLBP) has been widely used for dynamic texture
(DT) recognition. Hashing Pixel-Difference Vectors (PDVs) into binary codes before forming …

Vehicle classification using machine learning is introduced in numerous application areas
such as traffic management in foggy and rainy weather, vehicle recognition in driver-free …

Deep neural networks have been applied to audio spectrograms for respiratory sound
classification. Existing models often treat the spectrogram as a synthetic image while …