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Beyond supervised learning for pervasive healthcare
The integration of machine/deep learning and sensing technologies is transforming
healthcare and medical practice. However, inherent limitations in healthcare data, namely …
healthcare and medical practice. However, inherent limitations in healthcare data, namely …
Topological persistence guided knowledge distillation for wearable sensor data
Deep learning methods have achieved a lot of success in various applications involving
converting wearable sensor data to actionable health insights. A common application areas …
converting wearable sensor data to actionable health insights. A common application areas …
[PDF][PDF] Edge device for movement pattern classification using neural network algorithms
Portable electronic systems allow the analysis and monitoring of continuous time signals,
such as human activity, integrating deep learning techniques with cloud computing, causing …
such as human activity, integrating deep learning techniques with cloud computing, causing …
Leveraging angular distributions for improved knowledge distillation
Abstract Knowledge distillation as a broad class of methods has led to the development of
lightweight and memory efficient models, using a pre-trained model with a large capacity …
lightweight and memory efficient models, using a pre-trained model with a large capacity …
Logical reasoning for human activity recognition based on multisource data from wearable device
Smart wearable devices detection and recording of people's everyday activities is critical for
health monitoring, hel** persons with disabilities, and providing care for the elderly. Most …
health monitoring, hel** persons with disabilities, and providing care for the elderly. Most …
Topological knowledge distillation for wearable sensor data
Converting wearable sensor data to actionable health insights has witnessed large interest
in recent years. Deep learning methods have been utilized in and have achieved a lot of …
in recent years. Deep learning methods have been utilized in and have achieved a lot of …
S-KDGAN: Series-Knowledge Distillation With GANs for Anomaly Detection of Sensor Time-Series Data in Smart IoT
W Cheng, Y Li, T Ma - IEEE Sensors Journal, 2024 - ieeexplore.ieee.org
Nowadays, smart Internet of Things (IoT) technology has emerged as a new paradigm,
widely utilized across various fields of our lives. Sensors in smart IoT systems generate …
widely utilized across various fields of our lives. Sensors in smart IoT systems generate …
Constrained adaptive distillation based on topological persistence for wearable sensor data
Wearable sensor data analysis with persistence features generated by topological data
analysis (TDA) has achieved great success in various applications, and however, it suffers …
analysis (TDA) has achieved great success in various applications, and however, it suffers …
Wearable Sensor Data Classification for Identifying Missing Transmission Sequence Using Tree Learning
Wearable Sensor (WS) data accumulation and transmission are vital in analyzing the health
status of patients and elderly people remotely. Through specific time intervals, the …
status of patients and elderly people remotely. Through specific time intervals, the …
Improving WSN-based dataset using data augmentation for TSCH protocol performance modeling
This study addresses the problem of inadequate datasets in Time-Slotted Channel Hop**
(TSCH) protocol in Wireless Sensor Networks (WSN) by introducing a viable machine …
(TSCH) protocol in Wireless Sensor Networks (WSN) by introducing a viable machine …