Multi-input CNN-GRU based human activity recognition using wearable sensors

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Data Intensity-Based Feature Selection Protocol for Sensor-Based HAR System

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A Variable Batch Size-Based Hybrid Deep Learning Framework for HAR in Uncontrolled Environments

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Personalized Human Activity Recognition Method Based on Federated Hierarchical Clustering Learning

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An Attention-Enhanced Spatiotemporal Deep Learning Framework for Human Activity Recognition

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A lightweight spatial-temporal network with frequency-range fusion for edge-enabled FMCW radar human activity recognition

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Human Activity Recognition Using Smartphone Sensors and Deep Learning With Artificial Jellyfish Optimization

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Abnormal Activity Detection in Surveillance Using Optimized Cross Attention–Based Residual Autoencoder

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A Two-Stage Hybrid Ensemble Framework for Human Activity Recognition Toward Smart Healthcare and Intelligent Environments

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Context-integrated complex activity recognition with sector-level location encoding in residential environments

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An adaptive attention residual convolutional LSTM network for robust human activity recognition in healthy aging

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Time series anomaly detection models with contrastive representation learning

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Enhancing human activity recognition through GAN-augmented data and multi-branch CNN-LSTM networks

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Optimizing Human Activity Recognition with Ensemble Deep Learning on Wearable Sensor Data

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Preprocessing Strategies for Animal Behavior Classification Using Inertial Sensors: Effects of Filtering, Normalization, and Data Representation

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Activity contextualisation and terrain classification via wearables in Parkinson’s

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A Deep Multiple Instance Multiple Label Learning Framework for Smartphone-Based Human Activity Recognition

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ASN: Activity Sensing Network for Daily Life Detection Through Fusion of IMU and UWB Sensors

Kim, H., Kim, D., & Lim, Y. (2026) · Journal of Electrical Engineering and Technology · doi:10.1007/s42835-026-02988-2

Adaptive Quantization of CNNs for Spectrogram-Based Foreground Activity Classification

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Deep CNN-GRU Based Human Activity Recognition with Automatic Feature Extraction Using Smartphone and Wearable Sensors

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Single Input-Based CNN-LSTM and CNN-GRU Based HAR Using Wearable SensorsPreprint

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Single Input Single Head CNN-GRU-LSTM Architecture for Recognition of Human Activities

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Multi-sensor human activity recognition using CNN and GRU

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Deep learning based human activity recognition (HAR) using wearable sensor data

Gupta, S. (2021) · International Journal of Information Management Data Insights · doi:10.1016/j.jjimei.2021.100046 · Cited by 225