[HTML][HTML] Generalizable machine learning for stress monitoring from wearable devices: A systematic literature review
Introduction Wearable sensors have shown promise as a non-intrusive method for collecting
biomarkers that may correlate with levels of elevated stress. Stressors cause a variety of …
biomarkers that may correlate with levels of elevated stress. Stressors cause a variety of …
Data augmentation for time-series classification: An extensive empirical study and comprehensive survey
Z Gao, H Liu, L Li - arXiv preprint arXiv:2310.10060, 2023 - arxiv.org
Data Augmentation (DA) has become a critical approach in Time Series Classification
(TSC), primarily for its capacity to expand training datasets, enhance model robustness …
(TSC), primarily for its capacity to expand training datasets, enhance model robustness …
Benchmarking of synthetic network data: Reviewing challenges and approaches
Abstract The development of Network Intrusion Detection Systems (NIDS) requires labeled
network traffic, especially to train and evaluate machine learning approaches. Besides the …
network traffic, especially to train and evaluate machine learning approaches. Besides the …
Attention-enhanced conditional-diffusion-based data synthesis for data augmentation in machine fault diagnosis
PN Mueller - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
Data scarcity and class imbalance are pervasive challenges in machine fault diagnosis,
impeding the development and broad adaptation of accurate and reliable deep-learning …
impeding the development and broad adaptation of accurate and reliable deep-learning …
An Innovative Smart and Sustainable Low-Cost Irrigation System for Anomaly Detection Using Deep Learning
The agricultural sector faces several difficulties today in ensuring the safety of food supply,
including water scarcity. This study presents the design and development of a low-cost and …
including water scarcity. This study presents the design and development of a low-cost and …
Constrained Adversarial Learning and its applicability to Automated Software Testing: a systematic review
Every novel technology adds hidden vulnerabilities ready to be exploited by a growing
number of cyber-attacks. Automated software testing can be a promising solution to quickly …
number of cyber-attacks. Automated software testing can be a promising solution to quickly …
[HTML][HTML] An Explainable Deep Learning Approach for Stress Detection in Wearable Sensor Measurements
Stress has various impacts on the health of human beings. Recent success in wearable
sensor development, combined with advancements in deep learning to automatically detect …
sensor development, combined with advancements in deep learning to automatically detect …
Data augmentation for Human Activity Recognition with Generative Adversarial Networks
Currently, Human Activity Recognition (HAR) applications need a large volume of data to be
able to generalize to new users and environments. However, the availability of labeled data …
able to generalize to new users and environments. However, the availability of labeled data …
Hybrid deep learning model for wearable sensor‐based stress recognition for internet of medical things (IoMT) system
There are numerous, interrelated, and multi‐dimensional aspects that influence a person's
mental health, one of them being stress. Smart wearable technology having physiological …
mental health, one of them being stress. Smart wearable technology having physiological …
Machine Learning for Smart Irrigation in Agriculture: How Far along Are We?
The management of water resources is becoming increasingly important in several contexts,
including agriculture. Recently, innovative agricultural practices, advanced sensors, and …
including agriculture. Recently, innovative agricultural practices, advanced sensors, and …