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Daily Living Activity Recognition In-The-Wild: Modeling and Inferring Activity-Aware Human Contexts
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Predictive Analytics with Microsoft Azure Machine Learning
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Activity logging using lightweight classification techniques in mobile devices
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Activity Recognition in Smart Homes
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A Review and Taxonomy of Activity Recognition on Mobile Phones
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On the use of ensemble of classifiers for accelerometer-based activity recognition
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Real-time human activity recognition from accelerometer data using Convolutional Neural Networks
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Vectors of temporally correlated snippets for temporal action detection
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Physical activity classification in free-living conditions using smartphone accelerometer data and exploration of predicted results
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Toward a mobile crowdsensing system for road surface assessment
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RGB-D-based human motion recognition with deep learning: A survey
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Robust Human Activity Recognition using smartwatches and smartphones
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Deep learning algorithms for human activity recognition using mobile and wearable sensor networks: State of the art and research challenges
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A robust human activity recognition system using smartphone sensors and deep learning
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Mobile platform for affective context-aware systems
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Multi-view stacking for activity recognition with sound and accelerometer data
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User context recognition using smartphone sensors and classification models
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Continuous authentication of smartphone users based on activity pattern recognition using passive mobile sensing
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Hand, belt, pocket or bag: Practical activity tracking with mobile phones
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GCHAR: An efficient Group-based Context—aware human activity recognition on smartphone
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IDNet: Smartphone-based gait recognition with convolutional neural networks
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Deep learning for sensor-based activity recognition: A survey
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Probabilistic identification of sit-to-stand and stand-to-sit with a wearable sensor
inferredcites →https://doi.org/10.1016/j.pmcj.2017.07.001openalex-snapshot
Learning multi-level features for sensor-based human action recognition
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Daily Human Activities Recognition Using Heterogeneous Sensors from Smartphones
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Neural Networks for Pattern Recognition
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Assessing Daily Physical Activity in Older Adults: Unraveling the Complexity of Monitors, Measures, and Methods
inferredcites →https://doi.org/10.1109/cads.2017.8310680openalex-snapshot
PAMS: A new position-aware multi-sensor dataset for human activity recognition using smartphones
inferredcites →https://doi.org/10.1109/carpathiancc.2014.6843636openalex-snapshot
Human activity recognition using neural networks
inferredcites →https://doi.org/10.1109/dictap.2016.7543996openalex-snapshot
Micro-context recognition of sedentary behaviour using smartphone
inferredcites →https://doi.org/10.1109/fskd.2017.8393329openalex-snapshot
Human activity recognition based on random forests
inferredcites →https://doi.org/10.1109/i2mtc.2018.8409885openalex-snapshot
Smart home based ambient assisted living: Recognition of anomaly in the activity of daily living for an elderly living alone
inferredcites →https://doi.org/10.1109/icip.2015.7350781openalex-snapshot
UTD-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and a wearable inertial sensor
inferredcites →https://doi.org/10.1109/icsc.2018.00068openalex-snapshot
Context-Aware, Accurate, and Real Time Fall Detection System for Elderly People
inferredcites →https://doi.org/10.1109/ie.2012.39openalex-snapshot
Simple and Complex Activity Recognition through Smart Phones
inferredcites →https://doi.org/10.1109/ijcnn.2017.7966102openalex-snapshot
Deep neural networks for kitchen activity recognition
inferredcites →https://doi.org/10.1109/issnip.2015.7106915openalex-snapshot
Phone position/placement detection using accelerometer: Impact on activity recognition
inferredcites →https://doi.org/10.1109/jbhi.2016.2633287openalex-snapshot
A Deep Learning Approach to on-Node Sensor Data Analytics for Mobile or Wearable Devices
inferredcites →https://doi.org/10.1109/jbhi.2018.2875812openalex-snapshot
Gait Evaluation Using Procrustes and Euclidean Distance Matrix Analysis
inferredcites →https://doi.org/10.1109/jsen.2014.2370945openalex-snapshot
Wearable Sensors for Human Activity Monitoring: A Review
inferredcites →https://doi.org/10.1109/jsen.2016.2545708openalex-snapshot
A Comparative Study on Human Activity Recognition Using Inertial Sensors in a Smartphone
inferredcites →https://doi.org/10.1109/jsen.2018.2833745openalex-snapshot
A Data Fusion-Based Hybrid Sensory System for Older People’s Daily Activity and Daily Routine Recognition
inferredcites →https://doi.org/10.1109/jsen.2019.2898891openalex-snapshot
Activity-Aware Fall Detection and Recognition Based on Wearable Sensors
inferredcites →https://doi.org/10.1109/mc.2012.393openalex-snapshot
Opportunistic human activity and context recognition
inferredcites →https://doi.org/10.1109/mprv.2017.3971131openalex-snapshot
Recognizing Detailed Human Context in the Wild from Smartphones and Smartwatches
inferredcites →https://doi.org/10.1109/percomw.2015.7134104openalex-snapshot
Towards detection of bad habits by fusing smartphone and smartwatch sensors
inferredcites →https://doi.org/10.1109/tii.2018.2789925openalex-snapshot
Distilling the Knowledge From Handcrafted Features for Human Activity Recognition
inferredcites →https://doi.org/10.1109/tmc.2018.2841905openalex-snapshot
HuMAn: Complex Activity Recognition with Multi-Modal Multi-Positional Body Sensing
inferredcites →https://doi.org/10.1109/tpds.2013.2297309openalex-snapshot
Sherlock: Micro-Environment Sensing for Smartphones
inferredcites →https://doi.org/10.1145/2480741.2480744openalex-snapshot
A survey on smartphone-based systems for opportunistic user context recognition
inferredcites →https://doi.org/10.1145/2638728.2641673openalex-snapshot
Multi-sensor physical activity recognition in free-living
inferredcites →https://doi.org/10.1145/3158645openalex-snapshot
Activity Recognition with Evolving Data Streams
inferredcites →https://doi.org/10.1155/2016/9493047openalex-snapshot
A Context-Aware System Infrastructure for Monitoring Activities of Daily Living in Smart Home
inferredcites →https://doi.org/10.1155/2017/3090343openalex-snapshot
A Review on Human Activity Recognition Using Vision-Based Method
inferredcites →https://doi.org/10.1155/2021/6615695openalex-snapshot
Towards Activity Recognition through Multidimensional Mobile Data Fusion with a Smartphone and Deep Learning
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Monitoring of the daily living activities in smart home care
inferredcites →https://doi.org/10.15514/ispras-2021-33(1)-3openalex-snapshot
Machine Learning based Activity learning for Behavioral Contexts in Internet of Things
inferredcites →https://doi.org/10.1613/jair.953openalex-snapshot
SMOTE: Synthetic Minority Over-sampling Technique
inferredcites →https://doi.org/10.18293/seke2016-040openalex-snapshot
Combining Smartphone and Smartwatch Sensor Data in Activity Recognition Approaches: an Experimental Evaluation
inferredcites →https://doi.org/10.23919/aeit.2018.8577362openalex-snapshot
Neural Networks for Automated Smart Health Platforms oriented on Heart Predictive Diagnostic Big Data Systems
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Innovative and Assistive eHealth Technologies for Smart Therapeutic and Rehabilitation Outdoor Spaces for the Elderly Demographic
inferredcites →https://doi.org/10.28991/esj-2021-01254openalex-snapshot
Human Action Recognition in Videos using Convolution Long Short-Term Memory Network with Spatio-Temporal Networks
inferredcites →https://doi.org/10.3233/ais-160386openalex-snapshot
On-line human activity recognition from audio and home automation sensors: Comparison of sequential and non-sequential models in realistic Smart Homes1
inferredcites →https://doi.org/10.3389/fcomp.2021.759136openalex-snapshot
CSL-SHARE: A Multimodal Wearable Sensor-Based Human Activity Dataset
inferredcites →https://doi.org/10.3390/app11083414openalex-snapshot
COVID-19 Detection Empowered with Machine Learning and Deep Learning Techniques: A Systematic Review
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SIMADL: Simulated Activities of Daily Living Dataset
inferredcites →https://doi.org/10.3390/healthcare9080961openalex-snapshot
Artificial Intelligence for Hospital Health Care: Application Cases and Answers to Challenges in European Hospitals
inferredcites →https://doi.org/10.3390/s130709183openalex-snapshot
Optimal Placement of Accelerometers for the Detection of Everyday Activities
inferredcites →https://doi.org/10.3390/s131013099openalex-snapshot
Exploratory Data Analysis of Acceleration Signals to Select Light-Weight and Accurate Features for Real-Time Activity Recognition on Smartphones
inferredcites →https://doi.org/10.3390/s140203188openalex-snapshot
Optimal Sensor Placement for Measuring Physical Activity with a 3D Accelerometer
inferredcites →https://doi.org/10.3390/s140305687openalex-snapshot
Multi-Sensor Fusion for Enhanced Contextual Awareness of Everyday Activities with Ubiquitous Devices
inferredcites →https://doi.org/10.3390/s140610146openalex-snapshot
Fusion of Smartphone Motion Sensors for Physical Activity Recognition
inferredcites →https://doi.org/10.3390/s150102059openalex-snapshot
A Survey of Online Activity Recognition Using Mobile Phones
inferredcites →https://doi.org/10.3390/s150203721openalex-snapshot
Wearable Sensor Systems for Infants
inferredcites →https://doi.org/10.3390/s16040426openalex-snapshot
Complex Human Activity Recognition Using Smartphone and Wrist-Worn Motion Sensors
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An Analysis on Sensor Locations of the Human Body for Wearable Fall Detection Devices: Principles and Practice
inferredcites →https://doi.org/10.3390/s17010198openalex-snapshot
SisFall: A Fall and Movement Dataset
inferredcites →https://doi.org/10.3390/s17092043openalex-snapshot
Authentication of Smartphone Users Based on Activity Recognition and Mobile Sensing
inferredcites →https://doi.org/10.3390/s18020613openalex-snapshot
An Activity Recognition Framework Deploying the Random Forest Classifier and A Single Optical Heart Rate Monitoring and Triaxial Accelerometer Wrist-Band
inferredcites →https://doi.org/10.3390/s18082501openalex-snapshot
Preferred Placement and Usability of a Smart Textile System vs. Inertial Measurement Units for Activity Monitoring
inferredcites →https://doi.org/10.3390/s19143133openalex-snapshot
Classifying Diverse Physical Activities Using “Smart Garments”
inferredcites →https://doi.org/10.3390/s19143213openalex-snapshot
Human Activity Recognition Using Inertial Sensors in a Smartphone: An Overview
inferredcites →https://doi.org/10.3390/s19173808openalex-snapshot
Multi-Sensor Fusion for Activity Recognition—A Survey
inferredcites →https://doi.org/10.3390/s20030720openalex-snapshot
Internet of Things and Enhanced Living Environments: Measuring and Mapping Air Quality Using Cyber-physical Systems and Mobile Computing Technologies
inferredcites →https://doi.org/10.3390/s20051502openalex-snapshot
A Systematic Review on the Use of Wearable Body Sensors for Health Monitoring: A Qualitative Synthesis
inferredcites →https://doi.org/10.3390/s21020654openalex-snapshot
Moving the Lab into the Mountains: A Pilot Study of Human Activity Recognition in Unstructured Environments
inferredcites →https://doi.org/10.3390/s21030768openalex-snapshot
Activity Recognition for Ambient Assisted Living with Videos, Inertial Units and Ambient Sensors
inferredcites →https://doi.org/10.3390/s21030885openalex-snapshot
Personalized Human Activity Recognition Based on Integrated Wearable Sensor and Transfer Learning
inferredcites →https://doi.org/10.3390/s21051636openalex-snapshot
LSTM Networks Using Smartphone Data for Sensor-Based Human Activity Recognition in Smart Homes
inferredcites →https://doi.org/10.3390/s21062141openalex-snapshot
Sensor-Based Human Activity Recognition with Spatio-Temporal Deep Learning
inferredcites →https://doi.org/10.3390/s21165270openalex-snapshot
Daily Human Activity Recognition Using Non-Intrusive Sensors
inferredcites →https://doi.org/10.3837/tiis.2013.11.018openalex-snapshot
A Genetic Algorithm-based Classifier Ensemble Optimization for Activity Recognition in Smart Homes
inferredcites →https://doi.org/10.4018/978-1-5225-5484-4.ch011openalex-snapshot
Activity Recognition Using Ubiquitous Sensors
inferredcites →https://doi.org/10.4236/etsn.2017.61001openalex-snapshot
RFID Systems in Healthcare Settings and Activity of Daily Living in Smart Homes: A Review
inferredcites →https://doi.org/10.48550/arxiv.1604.08880openalex-snapshot
Deep, Convolutional, and Recurrent Models for Human Activity Recognition using Wearables
inferredcites →https://doi.org/10.5220/0005792401430151openalex-snapshot
The MobiAct Dataset: Recognition of Activities of Daily Living using Smartphones
inferredcites →https://doi.org/10.5555/1005332.1005336openalex-snapshot
In Defense of One-Vs-All Classification
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/s00607-025-01548-2openalex-snapshot
Smartphone sensor fusion for joint recognition of human activity and behavioral context
inferred← citeshttps://doi.org/10.1007/s10209-024-01173-4openalex-snapshot
A scoping review on serious games as rehabilitation technologies for ankle rehabilitation: game genres, game accessibility, and game usability
inferred← citeshttps://doi.org/10.1007/s11042-023-16423-5openalex-snapshot
In-depth analysis of design & development for sensor-based human activity recognition system
inferred← citeshttps://doi.org/10.1007/s11042-025-21053-0openalex-snapshot
Smartphone-based context-aware system for human activity recognition: dynamic and static methods
inferred← citeshttps://doi.org/10.1007/s12530-024-09570-zopenalex-snapshot
Deep Context Model (DCM): dual context-attention aware model for recognizing the heterogeneous human activities using smartphone sensors
inferred← citeshttps://doi.org/10.1007/s41060-026-01057-1openalex-snapshot
Multimodal activity recognition using separable convolutional long short-term memory
inferred← citeshttps://doi.org/10.1109/access.2024.3498852openalex-snapshot
A Novel Framework for Daily Life Activity and Context Recognition In-The-Wild Using Smartphone Inertial Sensors
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Identification of Human Activity and Associated Context Using Smartphone Inertial Sensors in Unrestricted Environment
inferred← citeshttps://doi.org/10.1109/case59546.2024.10711334openalex-snapshot
A data-driven approach for context definition in situation-aware wearable computing systems
inferred← citeshttps://doi.org/10.1109/ectidamtncon67592.2026.11460018openalex-snapshot
Real-Life Human Activity Recognition Based on Accelerometer Data From Smartphone Sensors Using CNN-BiGRU Model
inferred← citeshttps://doi.org/10.1109/icca59364.2023.10401417openalex-snapshot
Fuzzy FCA-based Elderly Activity Recognition
inferred← citeshttps://doi.org/10.1109/icomet57998.2023.10099271openalex-snapshot
A Framework for Daily Living Activity Recognition using Fusion of Smartphone Inertial Sensors Data
inferred← citeshttps://doi.org/10.1371/journal.pone.0286919openalex-snapshot
Less is more: Efficient behavioral context recognition using Dissimilarity-Based Query Strategy
inferred← citeshttps://doi.org/10.3390/app13084961openalex-snapshot
Human Activity Recognition by the Image Type Encoding Method of 3-Axial Sensor Data
inferred← citeshttps://doi.org/10.3390/mi14122204openalex-snapshot
Biosensor-Based Multimodal Deep Human Locomotion Decoding via Internet of Healthcare Things
inferred← citeshttps://doi.org/10.3390/s23125756openalex-snapshot
A Study on the Influence of Sensors in Frequency and Time Domains on Context Recognition
inferred← citeshttps://doi.org/10.3390/s23136040openalex-snapshot
Human Action Recognition in Smart Living Services and Applications: Context Awareness, Data Availability, Personalization, and Privacy
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