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: The problem we focused on in this article is sensor-based generalized few-shot activity recognition. In this problem, each of the predefined activity classes (i.e., base classes) has ...

Trevis Williams is eight inches taller than a man accused of flashing a woman in Union Square in February. The police arrested him anyway. Credit...Natalie Keyssar for The New York Times Supported by ...

Both for research and medical purposes, researchers have spent decades pushing the limits of microscopy to produce ever deeper and sharper images of brain activity, not only in the cortex but also in ...

Contactless Human Activity Recognition (HAR) has played a critical role in smart healthcare and elderly care homes to monitor patient behavior, detect falls or abnormal activities in real time. The ...

ABSTRACT: With technological advancements and increasing user demands, human action recognition plays a pivotal role in the field of human-computer interaction. Among various sensing devices, WiFi ...

Abstract: This study introduces a novel representation learning method to enhance unsupervised deep clustering in Human Activity Recognition (HAR). Traditional unsupervised deep clustering methods ...