On the public citation graph

A Novel Multi-Stage Training Approach for Human Activity Recognition From Multimodal Wearable Sensor Data Using Deep Neural Network

https://doi.org/10.1109/jsen.2020.3015781

0 signed · 85 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.

Claim with ORCID

Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/cpa.21413openalex-snapshot

Group Invariant Scattering

inferredcites →https://doi.org/10.1007/978-3-540-77690-1_2openalex-snapshot

Activity Recognition from On-Body Sensors: Accuracy-Power Trade-Off by Dynamic Sensor Selection

inferredcites →https://doi.org/10.1016/j.asoc.2015.01.025openalex-snapshot

On the use of ensemble of classifiers for accelerometer-based activity recognition

inferredcites →https://doi.org/10.1016/j.future.2019.05.059openalex-snapshot

A blockchain-based fog computing framework for activity recognition as an application to e-Healthcare services

inferredcites →https://doi.org/10.1016/j.neucom.2019.06.051openalex-snapshot

A hybrid deep convolutional and recurrent neural network for complex activity recognition using multimodal sensors

inferredcites →https://doi.org/10.1016/j.patcog.2016.08.003openalex-snapshot

Robust human activity recognition from depth video using spatiotemporal multi-fused features

inferredcites →https://doi.org/10.1109/access.2019.2927134openalex-snapshot

A Hybrid Deep Learning Model for Human Activity Recognition Using Multimodal Body Sensing Data

inferredcites →https://doi.org/10.1109/bsn.2016.7516235openalex-snapshot

Deep learning for human activity recognition: A resource efficient implementation on low-power devices

inferredcites →https://doi.org/10.1109/ccip.2016.7802880openalex-snapshot

Human activity recognition in cognitive environments using sequential ELM

inferredcites →https://doi.org/10.1109/jiot.2018.2873594openalex-snapshot

Wearable Computing for Internet of Things: A Discriminant Approach for Human Activity Recognition

inferredcites →https://doi.org/10.1109/jiot.2019.2920283openalex-snapshot

IoT Wearable Sensor and Deep Learning: An Integrated Approach for Personalized Human Activity Recognition in a Smart Home Environment

inferredcites →https://doi.org/10.1109/jsen.2017.2782492openalex-snapshot

Human Activity Classification in Smartphones Using Accelerometer and Gyroscope Sensors

inferredcites →https://doi.org/10.1109/percomw.2015.7134073openalex-snapshot

PEMAR: A pervasive middleware for activity recognition with smart phones

inferredcites →https://doi.org/10.1109/smc.2015.263openalex-snapshot

A Deep Learning Approach to Human Activity Recognition Based on Single Accelerometer

inferredcites →https://doi.org/10.1109/ssci.2015.199openalex-snapshot

Multivariate Time Series Classification Using Dynamic Time Warping Template Selection for Human Activity Recognition

inferredcites →https://doi.org/10.1117/12.2309486openalex-snapshot

Classification of time-series images using deep convolutional neural networks

inferredcites →https://doi.org/10.1145/2370216.2370438openalex-snapshot

USC-HAD

inferredcites →https://doi.org/10.1145/2733373.2806333openalex-snapshot

Human Activity Recognition Using Wearable Sensors by Deep Convolutional Neural Networks

inferredcites →https://doi.org/10.1145/3090076openalex-snapshot

Ensembles of Deep LSTM Learners for Activity Recognition using Wearables

inferredcites →https://doi.org/10.1145/3136755.3136817openalex-snapshot

Data augmentation of wearable sensor data for parkinson’s disease monitoring using convolutional neural networks

inferredcites →https://doi.org/10.1155/2015/140820openalex-snapshot

Human Activity Recognition Based on the Hierarchical Feature Selection and Classification Framework

inferredcites →https://doi.org/10.3390/s16010115openalex-snapshot

Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition

inferredcites →https://doi.org/10.3390/s17112556openalex-snapshot

Deep Recurrent Neural Networks for Human Activity Recognition

inferredcites →https://doi.org/10.3390/s19030458openalex-snapshot

Human Physical Activity Recognition Using Smartphone Sensors

inferredcites →https://doi.org/10.3390/s19030546openalex-snapshot

A Hierarchical Deep Fusion Framework for Egocentric Activity Recognition using a Wearable Hybrid Sensor System

inferredcites →https://doi.org/10.3390/s19030621openalex-snapshot

Smartphone-Based Activity Recognition for Indoor Localization Using a Convolutional Neural Network

inferredcites →https://doi.org/10.3390/s19071716openalex-snapshot

Sensor Data Acquisition and Multimodal Sensor Fusion for Human Activity Recognition Using Deep Learning

inferredcites →https://doi.org/10.48550/arxiv.1511.04664openalex-snapshot

Deep Activity Recognition Models with Triaxial Accelerometers

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4779157openalex-extracted

Methodology for Smartwatch-Based Complex Human Activity Recognition in Production Systems

inferred← citeshttps://doi.org/10.2139/ssrn.4792141openalex-extracted

Activity Recognition within a Manufacturing System: A Comparison of Logic Programming, Machine Learning, and Combinatorial Optimization Based Methods

inferred← citeshttps://doi.org/10.1007/978-3-030-91738-8_4openalex-snapshot

Human Activity Recognition Using Stacked LSTM

inferred← citeshttps://doi.org/10.1007/978-981-19-7524-0_36openalex-snapshot

2D Convolutional LSTM-Based Approach for Human Action Recognition on Various Sensor Data

inferred← citeshttps://doi.org/10.1007/978-981-99-8148-9_22openalex-snapshot

Knowledge-Distillation-Warm-Start Training Strategy for Lightweight Super-Resolution Networks

inferred← citeshttps://doi.org/10.1007/s00371-021-02166-7openalex-snapshot

A survey on deep multimodal learning for computer vision: advances, trends, applications, and datasets

inferred← citeshttps://doi.org/10.1007/s00521-023-08307-4openalex-snapshot

Physiotherapy-based human activity recognition using deep learning

inferred← citeshttps://doi.org/10.1007/s10489-022-03485-5openalex-snapshot

Knowledge transfer via distillation from time and frequency domain for time series classification

inferred← citeshttps://doi.org/10.1007/s11042-024-18599-wopenalex-snapshot

Outdoor activity classification using smartphone based inertial sensor measurements

inferred← citeshttps://doi.org/10.1007/s42835-022-00997-5openalex-snapshot

A New Activation Function with LSA for LNNA Based Hand Gesture Detection and its Application in Human-MAV Interaction

inferred← citeshttps://doi.org/10.1016/b978-0-443-26765-9.00007-xopenalex-snapshot

Deep learning for wearable sensor data analysis

inferred← citeshttps://doi.org/10.1016/j.cmpb.2026.109622openalex-snapshot

Activity contextualisation and terrain classification via wearables in Parkinson’s

inferred← citeshttps://doi.org/10.1016/j.compbiomed.2022.106060openalex-snapshot

Human activity recognition using tools of convolutional neural networks: A state of the art review, data sets, challenges, and future prospects

inferred← citeshttps://doi.org/10.1016/j.engappai.2026.114023openalex-snapshot

Temporal-spatial parallel multiscale network with sparse three-channel mixed attention for wearable sensor-based human activity recognition

inferred← citeshttps://doi.org/10.1016/j.engappai.2026.115787openalex-snapshot

Real-time recognition of multivariate event-based time series on embedded devices using recurrent neural networks: A practical study

inferred← citeshttps://doi.org/10.1016/j.eswa.2026.132415openalex-snapshot

Deep learning for human activity recognition: A comprehensive review of architectures, performance, and challenges across five sensory datasets

inferred← citeshttps://doi.org/10.1038/s41598-025-16180-5openalex-snapshot

Advanced smart human activity recognition system for disabled people using artificial intelligence with snake optimizer techniques

inferred← citeshttps://doi.org/10.1049/bme2.12115openalex-snapshot

Deep features fusion for user authentication based on human activity

inferred← citeshttps://doi.org/10.1061/jpcfev.cfeng-5198openalex-snapshot

Genetic Feature Selection and Multistage Deep Learning for Bridge Substructure Condition Prediction

inferred← citeshttps://doi.org/10.1080/03772063.2023.2248955openalex-snapshot

Multimodal Deep Learning for Activity Detection from IoT Sensors

inferred← citeshttps://doi.org/10.1109/access.2021.3122298openalex-snapshot

HiHAR: A Hierarchical Hybrid Deep Learning Architecture for Wearable Sensor-Based Human Activity Recognition

inferred← citeshttps://doi.org/10.1109/access.2022.3222562openalex-snapshot

Web Services for Collaboration Analysis With IoT Badges

inferred← citeshttps://doi.org/10.1109/aeeca59734.2023.00075openalex-snapshot

A CNN-LSTM-based Dual-task Neural Network for Power Operator Activity Detection

inferred← citeshttps://doi.org/10.1109/bigdata62323.2024.10825909openalex-snapshot

Smartwatch-Based Human Staff Activity Classification: A Use-Case Study in Internal Logistics Systems Utilizing AGVs

inferred← citeshttps://doi.org/10.1109/icievicivpr52578.2021.9564234openalex-snapshot

Human Action Recognition Based on a Sequential Deep Learning Model

inferred← citeshttps://doi.org/10.1109/icmlc56445.2022.9941334openalex-snapshot

Unsupervised Representation Learning Method In Sensor Based Human Activity Recognition

inferred← citeshttps://doi.org/10.1109/jiot.2023.3265937openalex-snapshot

A Multidimensional Parallel Convolutional Connected Network Based on Multisource and Multimodal Sensor Data for Human Activity Recognition

inferred← citeshttps://doi.org/10.1109/jsen.2022.3149948openalex-snapshot

MTMI-DCNN: A PSR-Based Method for Time Series Sensor Data Classification

inferred← citeshttps://doi.org/10.1109/jsen.2023.3303912openalex-snapshot

A BERT-Based Joint Channel–Temporal Modeling for Action Recognition

inferred← citeshttps://doi.org/10.1109/macs68476.2025.11453442openalex-snapshot

Multi-Stage Neural Network Model for Highprecision Crater Detection in High-Resolution Orbital Remote Sensing Data

inferred← citeshttps://doi.org/10.1109/punecon63413.2024.10894802openalex-snapshot

Establish an Innovative ML-enabled Human Activity Recognition through Edge Computing

inferred← citeshttps://doi.org/10.1109/tcyb.2021.3126831openalex-snapshot

Privacy-Preserving Cross-Environment Human Activity Recognition

inferred← citeshttps://doi.org/10.1109/tensymp68909.2026.11704026openalex-snapshot

Cross-Sensor Masked Self-Supervised Transformers for Domain-Adaptive Human Activity Recognition

inferred← citeshttps://doi.org/10.1109/tmm.2023.3340109openalex-snapshot

FedSea: Federated Learning via Selective Feature Alignment for Non-IID Multimodal Data

inferred← citeshttps://doi.org/10.1142/s021800142456007xopenalex-snapshot

Video Surveillance System-Based Human Activity Recognition Using Hierarchical Auto-Associative Polynomial Convolutional Neural Network with Garra Rufa Fish Optimization

inferred← citeshttps://doi.org/10.1142/s0218126625501956openalex-snapshot

Abnormal Network User Detection Method based on the Hybrid Neural Network from the Perspective of Multimodal Data Fusion

inferred← citeshttps://doi.org/10.13052/jicts2245-800x.1028openalex-snapshot

Basic Activity Recognition from Wearable Sensors Using a Lightweight Deep Neural Network

inferred← citeshttps://doi.org/10.1680/jsmic.21.00031openalex-snapshot

Automating excavator productivity measurement using deep learning

inferred← citeshttps://doi.org/10.2139/ssrn.5152077openalex-snapshot

A Dual-Branch Selective Co-Temporal Attention Framework for Human Activity Recognition Using Multisource and Multimodal Sensor Data

inferred← citeshttps://doi.org/10.2139/ssrn.6598003openalex-snapshot

Generalization in wearable-based human activity recognition: An explainable cross-dataset study of classical and deep learning models

inferred← citeshttps://doi.org/10.2478/jsiot-2024-0003openalex-snapshot

Wearable IoT and Artificial Intelligence Techniques for Leveraging the Human Activity Analysis

inferred← citeshttps://doi.org/10.32604/cmc.2024.052771openalex-snapshot

Enhancing Human Action Recognition with Adaptive Hybrid Deep Attentive Networks and Archerfish Optimization

inferred← citeshttps://doi.org/10.32604/iasc.2023.033542openalex-snapshot

Automatic Recognition of Construction Worker Activities Using Deep Learning Approaches and Wearable Inertial Sensors

inferred← citeshttps://doi.org/10.32920/25234624openalex-snapshot

Multimodal Sensor Fusion Frameworks With Application to Human Action Recognition

inferred← citeshttps://doi.org/10.32920/25234624.v1openalex-snapshot

Multimodal Sensor Fusion Frameworks With Application to Human Action Recognition

inferred← citeshttps://doi.org/10.3389/frai.2024.1424190openalex-snapshot

Wearable sensors based on artificial intelligence models for human activity recognition

inferred← citeshttps://doi.org/10.3390/a16020077openalex-snapshot

Transfer Learning Approach for Human Activity Recognition Based on Continuous Wavelet Transform

inferred← citeshttps://doi.org/10.3390/ai7010028openalex-snapshot

Multi-Modal Multi-Stage Multi-Task Learning for Occlusion-Aware Facial Landmark Localisation

inferred← citeshttps://doi.org/10.3390/electronics11010155openalex-snapshot

Towards Human Stress and Activity Recognition: A Review and a First Approach Based on Low-Cost Wearables

inferred← citeshttps://doi.org/10.3390/electronics12071509openalex-snapshot

Machine Learning and AI Technologies for Smart Wearables

inferred← citeshttps://doi.org/10.3390/s21062141openalex-snapshot

Sensor-Based Human Activity Recognition with Spatio-Temporal Deep Learning

inferred← citeshttps://doi.org/10.3390/s22083094openalex-snapshot

Deep Residual Network for Smartwatch-Based User Identification through Complex Hand Movements

inferred← citeshttps://doi.org/10.3390/s23125715openalex-snapshot

Human Activity Recognition Using Attention-Mechanism-Based Deep Learning Feature Combination

inferred← citeshttps://doi.org/10.3390/s23208449openalex-snapshot

Segment-Based Unsupervised Learning Method in Sensor-Based Human Activity Recognition

inferred← citeshttps://doi.org/10.3390/s26113420openalex-snapshot

Wearable Multifunctional Sensors for Human Activity Recognition

inferred← citeshttps://doi.org/10.35490/ec3.2021.153openalex-snapshot

Automating equipment productivity measurement using deep learning

inferred← citeshttps://doi.org/10.36930/40340413openalex-snapshot

Підхід до інтелектуалізації промислових підприємств на підставі розпізнавання складних видів діяльності персоналу.

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.