Deep learning for time series classification and extrinsic regression: A current survey
Time Series Classification and Extrinsic Regression are important and challenging machine
learning tasks. Deep learning has revolutionized natural language processing and computer …
learning tasks. Deep learning has revolutionized natural language processing and computer …
A comprehensive overview and comparative analysis on deep learning models: CNN, RNN, LSTM, GRU
Deep learning (DL) has emerged as a powerful subset of machine learning (ML) and
artificial intelligence (AI), outperforming traditional ML methods, especially in handling …
artificial intelligence (AI), outperforming traditional ML methods, especially in handling …
Energy-efficient and interpretable multisensor human activity recognition via deep fused lasso net
Utilizing data acquired by multiple wearable sensors can usually guarantee more accurate
recognition for deep learning based human activity recognition. However, an increased …
recognition for deep learning based human activity recognition. However, an increased …
A deep neural architecture for harmonizing 3-d input data analysis and decision making in medical imaging
Harmonizing the analysis of data, especially of 3-D image volumes, consisting of different
number of slices and annotated per volume, is a significant problem in training and using …
number of slices and annotated per volume, is a significant problem in training and using …
[HTML][HTML] Deep learning and transfer learning for device-free human activity recognition: A survey
Device-free activity recognition plays a crucial role in smart building, security, and human–
computer interaction, which shows its strength in its convenience and cost-efficiency …
computer interaction, which shows its strength in its convenience and cost-efficiency …
Review on human action recognition in smart living: Sensing technology, multimodality, real-time processing, interoperability, and resource-constrained processing
Smart living, a concept that has gained increasing attention in recent years, revolves around
integrating advanced technologies in homes and cities to enhance the quality of life for …
integrating advanced technologies in homes and cities to enhance the quality of life for …
Wireless sensing for material identification: A survey
As an application of fine-grained wireless sensing, RF-based material identification follows
the paradigm of RF computing that fetches the information during RF signal propagation …
the paradigm of RF computing that fetches the information during RF signal propagation …
End-edge-cloud collaborative computing for deep learning: A comprehensive survey
The booming development of deep learning applications and services heavily relies on
large deep learning models and massive data in the cloud. However, cloud-based deep …
large deep learning models and massive data in the cloud. However, cloud-based deep …
The applications of metaheuristics for human activity recognition and fall detection using wearable sensors: A comprehensive analysis
In this paper, we study the applications of metaheuristics (MH) optimization algorithms in
human activity recognition (HAR) and fall detection based on sensor data. It is known that …
human activity recognition (HAR) and fall detection based on sensor data. It is known that …
Hierarchical clustering-based personalized federated learning for robust and fair human activity recognition
Currently, federated learning (FL) can enable users to collaboratively train a global model
while protecting the privacy of user data, which has been applied to human activity …
while protecting the privacy of user data, which has been applied to human activity …