Abstract: Gesture recognition, a crucial technology in human-computer interaction, finds applications across various domains, including smart homes, automotive driver assistance systems, and more.

Abstract: Motor imagery (MI) electroencephalography (EEG) has become a cornerstone of brain-computer interface (BCI) research due to its non-invasive nature and high temporal resolution. However, ...

Abstract: The identification and analysis of human daily activities has garnered substantial attention in recent years, driven by its expansive applications in areas including healthcare, surveillance ...

The biggest chains in America are using facial recognition technology to try to stop shoplifting. But most customers are unaware their faces are being scanned while they shop. Facial recognition isn’t ...

👋 Welcome to 5 Things PM! Excessive alcohol use is pretty common, with 17% of adults in the US reporting binge drinking. Researchers explain why some people can’t stop — even when they know it’s ...

Abstract: Knowledge distillation (KD) is a predominant technique to streamline deep-learning-based recognition models for practical underwater deployments. However, existing KD methods for underwater ...

Abstract: Epilepsy is a widespread neurological disorder affecting approximately 50 million individuals globally, with a disproportionately high burden in low- and middle-income countries. It is ...

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 ...

Abstract: Deep learning-based object detectors have become increasingly critical in spectrogram-based wideband multi-signal detection, recognition, and time-frequency localization. Current methods ...

Abstract: Speaker recognition systems (SRS) play a vital role in identity authentication. At the same time, researchers have found that these systems are highly vulnerable to backdoor attacks, where ...

Abstract: Convolutional neural networks (CNNs) can automatically learn data patterns to express face images for facial expression recognition (FER). However, they may ignore effect of facial ...