artificial intelligence; deep learning;
Our paper presents RespiroDynamics: A Comprehensive Multimodal Respiratory Dataset, compiled from 60 participants, recorded in two sessions labelled ’rest’ and ’exercise’. This dataset incorporates a variety of data types, including Red-Green-Blue (RGB) and Thermal videos, Heart Rate (HR), ECG readings and metadata, all synchronized with observed respiratory activities. Additionally, these data are enriched with reference values from the NHANES III (Hankinson- 1999) distribution.
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This dataset contains adversarial attacks on Deep Learning (DL) when it is employed for the classification of
wireless modulated communication signals. The attack is executed with an obfuscating waveform that is embedded in the
transmitted signal in such a way that prevents the extraction of clean data for training from a wireless eavesdropper. At the
same time it allows a legitimate receiver (LRx) to demodulate the data. The scheme works for both single carrier and multi-carrier
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