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 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: Hand gesture recognition(HGR) is a key technology in human-computer interaction and human communication. This paper presents a lightweight, parameter-free attention convolutional neural ...

Music is an essential part of human culture, but automatically classifying songs into genres is a challenging problem for computers. With the explosion of digital music libraries, manual tagging is ...

Abstract: Advancements in instrumentation and control systems for lower limb prostheses have substantially improved mobility for amputees. However, significant challenges persist when users encounter ...

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 ...

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