Deep learning for human activity recognition: A comprehensive review of architectures, performance, and challenges across five sensory datasets
- 20 April 2026
- journal article
- review article
- Published by Elsevier in Expert Systems with Applications
- Vol. 323
Abstract
No abstract availableFunding Information
- Federación Española de Enfermedades Raras
This publication has 151 references indexed in Scilit:
- CNN-SLSTM framework for human activity recognition using wearable sensor dataNeural Computing and Applications, 2025
- Human Activity Recognition: Approaches, Datasets, Applications, and Challenges2023
- A modified Adam algorithm for deep neural network optimizationNeural Computing and Applications, 2023
- Human activity recognition from sensor data using spatial attention-aided CNN with genetic algorithmNeural Computing and Applications, 2022
- A multibranch CNN-BiLSTM model for human activity recognition using wearable sensor dataThe Visual Computer, 2021
- Multi-input CNN-GRU based human activity recognition using wearable sensorsComputing, 2021
- Deep learning based multimodal complex human activity recognition using wearable devicesApplied Intelligence, 2020
- A GAN‐based data augmentation method for human activity recognition via the caching abilityInternet Technology Letters, 2020
- Sensor-Based Benchmark Datasets: Comparison and Analysis2020
- Human Activity Recognition Based on Wearable Sensor Using Hierarchical Deep LSTM NetworksCircuits, Systems, and Signal Processing, 2019