Sakorn Mekruksavanich

Orcid: 0000-0002-3735-4262

According to our database1, Sakorn Mekruksavanich authored at least 42 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Deep Residual Network with a CBAM Mechanism for the Recognition of Symmetric and Asymmetric Human Activity Using Wearable Sensors.
Symmetry, May, 2024

Recognition of sports and daily activities through deep learning and convolutional block attention.
PeerJ Comput. Sci., 2024

Identifying Smartphone Users Based on Activities in Daily Living Using Deep Neural Networks.
Inf., 2024

Improving Neural Network-Based Multi-Label Classification With Pattern Loss Penalties.
IEEE Access, 2024

Detecting Face-Touching Gestures with Smartwatches and Deep Learning Networks.
Proceedings of the 47th International Conference on Telecommunications and Signal Processing, 2024

Harnessing Deep Learning for Activity Recognition in Seniors' Daily Routines with Wearable Sensors.
Proceedings of the 47th International Conference on Telecommunications and Signal Processing, 2024

Leveraging Residual Deep Neural Networks and Multi-Device Sensors for Heterogeneous Activity Recognition.
Proceedings of the 47th International Conference on Telecommunications and Signal Processing, 2024

A Hybrid Residual CNN with Channel Attention Mechanism for Continuous User Identification Using Wearable Motion Sensors.
Proceedings of the 47th International Conference on Telecommunications and Signal Processing, 2024

Deep Learning Networks for Human Knee Abnormality Detection Based on Surface EMG Signals.
Proceedings of the 47th International Conference on Telecommunications and Signal Processing, 2024

Efficient Residual Neural Network for Human Activity Recognition using WiFi CSI Signals.
Proceedings of the 2024 9th International Conference on Information and Education Innovations, 2024

Optimizing On-Body Sensor Placements for Deep Learning-Driven Human Activity Recognition.
Proceedings of the Computational Science and Its Applications - ICCSA 2024, 2024

Elevating Wearable Sensor Authentication with Hybrid Deep Learning and Squeeze-and-Excitation.
Proceedings of the Computational Science and Its Applications - ICCSA 2024, 2024

Modeling Life Insurance Business Growth in Thailand using SARIMAX and Multilayer Perceptron.
Proceedings of the 16th International Conference on Computer and Automation Engineering, 2024

2023
Effective Detection of Epileptic Seizures through EEG Signals Using Deep Learning Approaches.
Mach. Learn. Knowl. Extr., December, 2023

A Deep Learning Network with Aggregation Residual Transformation for Human Activity Recognition Using Inertial and Stretch Sensors.
Comput., June, 2023

A Comparative Study of Deep Learning Robustness for Sensor-based Human Activity Recognition.
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.
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.
Proceedings of the 46th International Conference on Telecommunications and Signal Processing, 2023

Deep Learning Approaches for Epileptic Seizures Recognition based on EEG Signal.
Proceedings of the 46th International Conference on Telecommunications and Signal Processing, 2023

Human Activity Recognition in Logistics Using Wearable Sensors and Deep Residual Network.
Proceedings of the IEEE Region 10 Conference, 2023

Deep Learning Networks for Complex Activity Recognition Based on Wrist-Worn Sensor.
Proceedings of the IEEE Region 10 Conference, 2023

Classifying Activities of Electrical Line Workers Based on Deep Learning Approaches Using Wrist-Worn Sensor.
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.
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.
Sensors, 2022

ResNet-SE: Channel Attention-Based Deep Residual Network for Complex Activity Recognition Using Wrist-Worn Wearable Sensors.
IEEE Access, 2022

Deep Residual Networks for Human Activity Recognition based on Biosignals from Wearable Devices.
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.
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.
Proceedings of the Multi-disciplinary Trends in Artificial Intelligence, 2022

Recognizing Driver Activities Using Deep Learning Approaches Based on Smartphone Sensors.
Proceedings of the Multi-disciplinary Trends in Artificial Intelligence, 2022

Hierarchical Human Activity Recognition Based on Smartwatch Sensors Using Branch Convolutional Neural Networks.
Proceedings of the Multi-disciplinary Trends in Artificial Intelligence, 2022

Multi-resolution CNN for Lower Limb Movement Recognition Based on Wearable Sensors.
Proceedings of the Multi-disciplinary Trends in Artificial Intelligence, 2022

A Hybrid Deep Neural Network for Classifying Transportation Modes based on Human Activity Vibration.
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.
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.
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.
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.
Sensors, 2021

LSTM Networks Using Smartphone Data for Sensor-Based Human Activity Recognition in Smart Homes.
Sensors, 2021

Location-based Daily Human Activity Recognition using Hybrid Deep Learning Network.
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.
Symmetry, 2020

Smartwatch-based Human Activity Recognition Using Hybrid LSTM Network.
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.
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.
Proceedings of the 13th International Conference on Signal-Image Technology & Internet-Based Systems, 2017


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