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Deriving Effective Human Activity Recognition Systems through Objective Task Complexity Assessment

https://doi.org/10.1145/3432227
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What this work says

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

inferredcites →https://doi.org/10.1007/s10115-016-1003-3openalex-snapshot
Can classification performance be predicted by complexity measures? A study using microarray data
inferredcites →https://doi.org/10.1016/j.parkreldis.2016.09.009openalex-snapshot
Unsupervised home monitoring of Parkinson's disease motor symptoms using body-worn accelerometers
inferredcites →https://doi.org/10.1016/j.pmcj.2010.11.007openalex-snapshot
Rapid specification and automated generation of prompting systems to assist people with dementia
inferredcites →https://doi.org/10.1017/s0033291716002166openalex-snapshot
A study of wrist-worn activity measurement as a potential real-world biomarker for late-life depression
inferredcites →https://doi.org/10.1109/34.990132openalex-snapshot
Complexity measures of supervised classification problems
inferredcites →https://doi.org/10.1109/ebbt.2019.8742042openalex-snapshot
Freezing of Gait (FoG) Detection Using Logistic Regression in Parkinson's Disease from Acceleration Signals
inferredcites →https://doi.org/10.1109/iccsce.2014.7072750openalex-snapshot
Human activity recognition: A review
inferredcites →https://doi.org/10.1109/icme.2000.869596openalex-snapshot
Hand gesture recognition of a mobile device user
inferredcites →https://doi.org/10.1109/icpr.2000.906015openalex-snapshot
Measuring the complexity of classification problems
inferredcites →https://doi.org/10.1109/ijcnn.2015.7280302openalex-snapshot
An insight on complexity measures and classification in microarray data
inferredcites →https://doi.org/10.1109/inss.2010.5573462openalex-snapshot
Collecting complex activity datasets in highly rich networked sensor environments
inferredcites →https://doi.org/10.1109/iswc.2012.13openalex-snapshot
Introducing a New Benchmarked Dataset for Activity Monitoring
inferredcites →https://doi.org/10.1109/mc.2018.2381112openalex-snapshot
Deep Learning for Human Activity Recognition in Mobile Computing
inferredcites →https://doi.org/10.1109/mprv.2008.40openalex-snapshot
Wearable Activity Tracking in Car Manufacturing
inferredcites →https://doi.org/10.1109/rfid.2013.6548154openalex-snapshot
Sensor enabled wearable RFID technology for mitigating the risk of falls near beds
inferredcites →https://doi.org/10.1109/titb.2009.2036165openalex-snapshot
Wearable Assistant for Parkinson’s Disease Patients With the Freezing of Gait Symptom
inferredcites →https://doi.org/10.1145/2370216.2370276openalex-snapshot
Automatic assessment of problem behavior in individuals with developmental disabilities
inferredcites →https://doi.org/10.1145/2370216.2370438openalex-snapshot
USC-HAD
inferredcites →https://doi.org/10.1145/2493988.2494353openalex-snapshot
On preserving statistical characteristics of accelerometry data using their empirical cumulative distribution
inferredcites →https://doi.org/10.1145/2499621openalex-snapshot
A tutorial on human activity recognition using body-worn inertial sensors
inferredcites →https://doi.org/10.1145/2809695.2809718openalex-snapshot
Smart Devices are Different
inferredcites →https://doi.org/10.1145/2829875.2829930openalex-snapshot
Basketball Activity Recognition using Wearable Inertial Measurement Units
inferredcites →https://doi.org/10.1145/3090076openalex-snapshot
Ensembles of Deep LSTM Learners for Activity Recognition using Wearables
inferredcites →https://doi.org/10.1145/3267242.3267246openalex-snapshot
On specialized window lengths and detector based human activity recognition
inferredcites →https://doi.org/10.1145/3267242.3267258openalex-snapshot
Adding structural characteristics to distribution-based accelerometer representations for activity recognition using wearables
inferredcites →https://doi.org/10.1145/3314399openalex-snapshot
Towards Reliable, Automated General Movement Assessment for Perinatal Stroke Screening in Infants Using Wearable Accelerometers
inferredcites →https://doi.org/10.1145/3328935openalex-snapshot
Automated Detection of Infant Holding Using Wearable Sensing
inferredcites →https://doi.org/10.1145/3341163.3347727openalex-snapshot
On the role of features in human activity recognition
inferredcites →https://doi.org/10.1145/3341163.3347744openalex-snapshot
Handling annotation uncertainty in human activity recognition
inferredcites →https://doi.org/10.1162/neco.1994.6.5.851openalex-snapshot
Measuring the VC-Dimension of a Learning Machine
inferredcites →https://doi.org/10.3390/data3020011openalex-snapshot
SIMADL: Simulated Activities of Daily Living Dataset
inferredcites →https://doi.org/10.3390/s150613159openalex-snapshot
mDurance: A Novel Mobile Health System to Support Trunk Endurance Assessment
inferredcites →https://doi.org/10.3390/s16010115openalex-snapshot
Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition
inferredcites →https://doi.org/10.4108/icst.mobicase.2014.257786openalex-snapshot
Convolutional Neural Networks for Human Activity Recognition using Mobile Sensors

What points at this work

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

inferred← citeshttps://doi.org/10.1007/978-3-030-89691-1_34openalex-snapshot
Video and Image Complexity in Human Action Recognition
inferred← citeshttps://doi.org/10.1007/978-3-658-37344-3_15openalex-snapshot
Anwendung von Human Activity Recognition im Unternehmenskontext – Ein Konzept für die Zukunft?
inferred← citeshttps://doi.org/10.1016/j.dajour.2023.100282openalex-snapshot
Enhancing human activity recognition using features reduction in IoT edge and Azure cloud
inferred← citeshttps://doi.org/10.1109/abc61795.2024.10651685openalex-snapshot
Maintenance Required: Updating and Extending Bootstrapped Human Activity Recognition Systems for Smart Homes
inferred← citeshttps://doi.org/10.1109/mprv.2022.3160063openalex-snapshot
Stepping Into the Next Decade of Ubiquitous and Pervasive Computing: UbiComp and ISWC 2021
inferred← citeshttps://doi.org/10.1109/percomworkshops56833.2023.10150267openalex-snapshot
If only we had more data!: Sensor-Based Human Activity Recognition in Challenging Scenarios
inferred← citeshttps://doi.org/10.1145/3550294openalex-snapshot
Bootstrapping Human Activity Recognition Systems for Smart Homes from Scratch
inferred← citeshttps://doi.org/10.1145/3550299openalex-snapshot
Assessing the State of Self-Supervised Human Activity Recognition Using Wearables
inferred← citeshttps://doi.org/10.1145/3550319openalex-snapshot
Predicting Performance Improvement of Human Activity Recognition Model by Additional Data Collection
inferred← citeshttps://doi.org/10.1145/3712278openalex-snapshot
Layout-Agnostic Human Activity Recognition in Smart Homes through Textual Descriptions Of Sensor Triggers (TDOST)
inferred← citeshttps://doi.org/10.3390/s23187729openalex-snapshot
The Lifespan of Human Activity Recognition Systems for Smart Homes
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