This project implements a hybrid deep learning model combining Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks for human activity recognition using sensor data from ...
Abstract: Human action recognition (HAR) methods based on ultra-wideband (UWB) multiple-input–multiple-output (MIMO) radar have demonstrated substantial potential in complex environments. However, the ...
Abstract: In wireless communications, radio frequency fingerprint identification (RFFI) leverages unique hardware characteristics for device recognition. This paper proposes an innovative few-shot ...
Abstract: In this work, we introduce the Federated Quantum Kernel-Based Long Short-term Memory (Fed-QK-LSTM) framework, integrating the quantum kernel methods and Long Shortterm Memory into federated ...
It’s time to uncork the prosecco and maybe order a plate of tagliatelle al ragù for the table. Italy has a very tasty reason to celebrate: Its national cuisine has become the first entire gastronomic ...
Abstract: Advancements in instrumentation and control systems for lower limb prostheses have substantially improved mobility for amputees. However, significant challenges persist when users encounter ...
The prospect of Paramount’s buying Warner Bros. Discovery had led CNN journalists to wonder if the channel may be combined with CBS News. Instead, CNN will remain in a separate corporate entity. By ...
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 ...
Abstract: Human activity recognition (HAR) using millimeter-wave (mmWave) radar has gained attention as a contactless and privacy-preserving sensing method that remains effective under low lighting ...
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