Sakorn Mekruksavanich

Phatthanaphong Chomphuwiset

Inf., 2024

Improving Neural Network-Based Multi-Label Classification With Pattern Loss Penalties.

[BibT_eX]

[DOI]

Worawith Sangkatip

Kaveepoj Bunluewong

Emmanuel Okafor

Olarik Surinta

IEEE Access, 2024

2023

Effective Detection of Epileptic Seizures through EEG Signals Using Deep Learning Approaches.

[BibT_eX]

[DOI]

Mach. Learn. Knowl. Extr., December, 2023

A Deep Learning Network with Aggregation Residual Transformation for Human Activity Recognition Using Inertial and Stretch Sensors.

[BibT_eX]

[DOI]

Comput., June, 2023

A Comparative Study of Deep Learning Robustness for Sensor-based Human Activity Recognition.

[BibT_eX]

[DOI]

Proceedings of the 46th International Conference on Telecommunications and Signal Processing, 2023

Free-Weight Exercise Activity Recognition using Deep Residual Neural Network based on Sensor Data from In-Ear Wearable Devices.

[BibT_eX]

[DOI]

Proceedings of the 46th International Conference on Telecommunications and Signal Processing, 2023

Position-aware Human Activity Recognition with Smartphone Sensors based on Deep Learning Approaches.

[BibT_eX]

[DOI]

Proceedings of the 46th International Conference on Telecommunications and Signal Processing, 2023

Deep Learning Approaches for Epileptic Seizures Recognition based on EEG Signal.

[BibT_eX]

[DOI]

Proceedings of the 46th International Conference on Telecommunications and Signal Processing, 2023

Human Activity Recognition in Logistics Using Wearable Sensors and Deep Residual Network.

[BibT_eX]

[DOI]

Datchakorn Tancharoen

Proceedings of the IEEE Region 10 Conference, 2023

Deep Learning Networks for Complex Activity Recognition Based on Wrist-Worn Sensor.

[BibT_eX]

[DOI]

Proceedings of the IEEE Region 10 Conference, 2023

Classifying Activities of Electrical Line Workers Based on Deep Learning Approaches Using Wrist-Worn Sensor.

[BibT_eX]

[DOI]

Proceedings of the 20th IEEE International Joint Conference on Computer Science and Software Engineering, 2023

Enhancing Sensor-Based Human Activity Recognition using Efficient Channel Attention.

[BibT_eX]

[DOI]

Proceedings of the 2023 IEEE SENSORS, Vienna, Austria, October 29 - Nov. 1, 2023, 2023

2022

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

[BibT_eX]

[DOI]

Sensors, 2022

ResNet-SE: Channel Attention-Based Deep Residual Network for Complex Activity Recognition Using Wrist-Worn Wearable Sensors.

[BibT_eX]

[DOI]

Kanokwan Sitthithakerngkiet

Phichai Youplao

Preecha P. Yupapin

IEEE Access, 2022

Deep Residual Networks for Human Activity Recognition based on Biosignals from Wearable Devices.

[BibT_eX]

[DOI]

Proceedings of the 45th International Conference on Telecommunications and Signal Processing, 2022

Smartwatch-based Eating Detection and Cutlery Classification using a Deep Residual Network with Squeeze-and-Excitation Module.

[BibT_eX]

[DOI]

Proceedings of the 45th International Conference on Telecommunications and Signal Processing, 2022

Wearable Fall Detection Based on Motion Signals Using Hybrid Deep Residual Neural Network.

[BibT_eX]

[DOI]

Proceedings of the Multi-disciplinary Trends in Artificial Intelligence, 2022

Recognizing Driver Activities Using Deep Learning Approaches Based on Smartphone Sensors.

[BibT_eX]

[DOI]

Proceedings of the Multi-disciplinary Trends in Artificial Intelligence, 2022

Hierarchical Human Activity Recognition Based on Smartwatch Sensors Using Branch Convolutional Neural Networks.

[BibT_eX]

[DOI]

Nagorn Maitrichit

Proceedings of the Multi-disciplinary Trends in Artificial Intelligence, 2022

Multi-resolution CNN for Lower Limb Movement Recognition Based on Wearable Sensors.

[BibT_eX]

[DOI]

Pitchaya Chotivatunyu

Proceedings of the Multi-disciplinary Trends in Artificial Intelligence, 2022

A Hybrid Deep Neural Network for Classifying Transportation Modes based on Human Activity Vibration.

[BibT_eX]

[DOI]

Ilsun You

Proceedings of the 14th International Conference on Knowledge and Smart Technology, 2022

A Novel Deep BiGRU-ResNet Model for Human Activity Recognition using Smartphone Sensors.

[BibT_eX]

[DOI]

Proceedings of the 19th International Joint Conference on Computer Science and Software Engineering, 2022

Deep Learning Models for Daily Living Activity Recognition based on Wearable Inertial Sensors.

[BibT_eX]

[DOI]

Proceedings of the 19th International Joint Conference on Computer Science and Software Engineering, 2022

A Deep Learning-based Model for Human Activity Recognition using Biosensors embedded into a Smart Knee Bandage.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Information Technology and Quantitative Management, 2022

2021

Deep Learning Approaches for Continuous Authentication Based on Activity Patterns Using Mobile Sensing.

[BibT_eX]

[DOI]

Sensors, 2021

LSTM Networks Using Smartphone Data for Sensor-Based Human Activity Recognition in Smart Homes.

[BibT_eX]

[DOI]

Sensors, 2021

Location-based Daily Human Activity Recognition using Hybrid Deep Learning Network.

[BibT_eX]

[DOI]

Chanon Promsakon

Proceedings of the 18th International Joint Conference on Computer Science and Software Engineering, 2021

2020

Enhanced Hand-Oriented Activity Recognition Based on Smartwatch Sensor Data Using LSTMs.

[BibT_eX]

[DOI]

Phichai Youplao

Preecha P. Yupapin

Symmetry, 2020

Smartwatch-based Human Activity Recognition Using Hybrid LSTM Network.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE Sensors, Rotterdam, The Netherlands, October 25-28, 2020, 2020

2017

Identifying Behavioral Design Flaws in Evolving Object-Oriented Software Using an Ontology-Based Approach.

[BibT_eX]

[DOI]

Proceedings of the 13th International Conference on Signal-Image Technology & Internet-Based Systems, 2017

Human Activity Recognition Using Triaxial Acceleration Data from Smartphone and Ensemble Learning.

[BibT_eX]

[DOI]