A new study developed a snore-source classification model that uses STFT spectrograms, pretrained CNN features, and an L2-regularized SVM to identify where snoring originates in the upper airway.
Abstract: Vision transformers have shown tremendous success in numerous computer vision applications; however, they have not been exploited for stress assessment using physiological signals such as ...
Abstract: Radar-based micro-Doppler spectrograms offer a robust representation for classifying aerial objects, particularly small Uncrewed Aerial Vehicles (UAVs), in scenarios where optical sensing is ...
1 Department of Computer and Instructional Technologies Education, Gazi Faculty of Education, Gazi University, Ankara, Türkiye. 2 Department of Forensic Informatics, Institute of Informatics, Gazi ...
The ESC-50 dataset is a labeled collection of 2000 environmental audio recordings suitable for benchmarking methods of environmental sound classification. The dataset consists of 5-second-long ...
The previous chirp detection algorithm was based entirely on manual extraction of multiple features across time and space, where anomalies on a all features at the same time were chirps. This approach ...
Alzheimer's disease (AD) and frontotemporal dementia (FTD) are major neurodegenerative disorders with characteristic EEG alterations. While most prior studies have focused on eyes-closed (EC) EEG, ...
Speech Emotion Recognition (SER) is crucial for enhancing human-computer interactions by enabling machines to understand and respond appropriately to human emotions. However, accurately recognizing ...
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