Wearable sensors for human activity recognition based on a self-attention CNN-BiLSTM model

Sensor-based human activity recognition using fuzzified deep CNN architecture with λmax method

(2022) Gomathi V. et al.   Sensor Review

LSTM Networks Using Smartphone Data for Sensor-Based Human Activity Recognition in Smart Homes

(2021) Sakorn Mekruksavanich et al.   SENSORS

Real-time multimodal ADL recognition using convolution neural networks

(2020) Danushka Madhuranga et al.   VISUAL COMPUTER

Deep ConvLSTM With Self-Attention for Human Activity Decoding Using Wearable Sensors

(2020) Satya P. Singh et al.   IEEE SENSORS JOURNAL

Attention-Based Convolutional Neural Network for Weakly Labeled Human Activities’ Recognition With Wearable Sensors

(2019) Kun Wang et al.   IEEE SENSORS JOURNAL

Deep Learning Models for Real-time Human Activity Recognition with Smartphones

(2019) Shaohua Wan et al.   MOBILE NETWORKS & APPLICATIONS

TSE-CNN: A Two-Stage End-to-End CNN for Human Activity Recognition

(2019) Jiahui Huang et al.   IEEE Journal of Biomedical and Health Informatics

Smartphone Sensor-Based Human Activity Recognition Using Feature Fusion and Maximum Full a Posteriori

(2019) Zhenghua Chen et al.   IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

Real-time human activity recognition from accelerometer data using Convolutional Neural Networks

(2018) Andrey Ignatov   APPLIED SOFT COMPUTING

WITS: an IoT-endowed computational framework for activity recognition in personalized smart homes

(2018) Lina Yao et al.   COMPUTING

Vision-Based Human Action Classification Using Adaptive Boosting Algorithm

(2018) Nabil Zerrouki et al.   IEEE SENSORS JOURNAL

Recent trends in machine learning for human activity recognition-A survey

(2018) Sreenivasan Ramasamy Ramamurthy et al.   Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery

Deep Learning for Fall Detection: 3D-CNN Combined with LSTM on Video Kinematic Data

(2018) Na Lu et al.   IEEE Journal of Biomedical and Health Informatics

LSTM Fully Convolutional Networks for Time Series Classification

(2018) Fazle Karim et al.   IEEE Access

Unobtrusive Monitoring to Detect Depression for Elderly With Chronic Illnesses

(2017) Jung-Yoon Kim et al.   IEEE SENSORS JOURNAL

Robust Human Activity Recognition Using Smartphone Sensors via CT-PCA and Online SVM

(2017) Zhenghua Chen et al.   IEEE Transactions on Industrial Informatics

Improving Activity Recognition Accuracy in Ambient-Assisted Living Systems by Automated Feature Engineering

(2017) Eftim Zdravevski et al.   IEEE Access

Hidden Markov model a tool for recognition of human contexts using sensors of smart mobile phone

(2016) Dulal Acharjee et al.   MICROSYSTEM TECHNOLOGIES-MICRO-AND NANOSYSTEMS-INFORMATION STORAGE AND PROCESSING SYSTEMS

Human Activity Recognition by Combining a Small Number of Classifiers

(2016) Alfredo Nazabal et al.   IEEE Journal of Biomedical and Health Informatics

An Unsupervised Approach for Automatic Activity Recognition Based on Hidden Markov Model Regression

(2013) Dorra Trabelsi et al.   IEEE Transactions on Automation Science and Engineering

Joint segmentation of multivariate time series with hidden process regression for human activity recognition

(2013) F. Chamroukhi et al.   NEUROCOMPUTING

Hierarchical, Multi-Sensor Based Classification of Daily Life Activities: Comparison with State-of-the-Art Algorithms Using a Benchmark Dataset

(2013) Heike Leutheuser et al.   PLoS One

Human Behavior Cognition Using Smartphone Sensors

(2013) Ling Pei et al.   SENSORS

Classification Accuracies of Physical Activities Using Smartphone Motion Sensors

(2012) Wanmin Wu et al.   JOURNAL OF MEDICAL INTERNET RESEARCH

Machine Learning Methods for Classifying Human Physical Activity from On-Body Accelerometers

(2010) Andrea Mannini et al.   SENSORS