Tatsuhito Hasegawa

Orcid: 0000-0002-0768-1406

According to our database1, Tatsuhito Hasegawa authored at least 30 papers between 2015 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Expanding the Horizons of 1-D Tasks: Leveraging 2-D Convolutional Neural Networks Pretrained by ImageNet.
IEEE Internet Things J., October, 2024

Estimation of Meal Residues Using Foundation Models.
Proceedings of the 13th IEEE Global Conference on Consumer Electronics, 2024

Background and Visual Feature-Aware Data Augmentation for FGIR via Image Generation.
Proceedings of the 13th IEEE Global Conference on Consumer Electronics, 2024

Data Augmentation using Foundation model for Fine-grained Fish Species Identification.
Proceedings of the 13th IEEE Global Conference on Consumer Electronics, 2024

2023
Segment-Based Unsupervised Learning Method in Sensor-Based Human Activity Recognition.
Sensors, October, 2023

Sensor-Based Activity Recognition Using Frequency Band Enhancement Filters and Model Ensembles.
Sensors, February, 2023

Easy Ensemble: Simple Deep Ensemble Learning for Sensor-Based Human Activity Recognition.
IEEE Internet Things J., 2023

2022
A Comparative Study: Toward an Effective Convolutional Neural Network Architecture for Sensor-Based Human Activity Recognition.
IEEE Access, 2022

Domain-Robust Pre-Training Method for the Sensor-Based Human Activity Recognition.
Proceedings of the International Conference on Machine Learning and Cybernetics, 2022

Unsupervised Representation Learning Method In Sensor Based Human Activity Recognition.
Proceedings of the International Conference on Machine Learning and Cybernetics, 2022

2021
Sensor-Based Human Activity Recognition Using Adaptive Class Hierarchy.
Sensors, 2021

Detection of Motion on a Trampoline with a Smartwatch.
Sensors, 2021

Smartphone Sensor-based Human Activity Recognition Robust to Different Sampling Rates.
CoRR, 2021

Octave Mix: Data Augmentation Using Frequency Decomposition for Activity Recognition.
IEEE Access, 2021

Effects of Different Activities on Learning Efficiency of m-Learning Users.
Proceedings of the 2021 IEEE International Conference on Engineering, 2021

2020
Fish Species Identification Using a CNN-based Multimodal Learning Method.
Proceedings of the IVSP '20: 2nd International Conference on Image, 2020

CNN-based Criteria for Classifying Artists by Illustration Style.
Proceedings of the IVSP '20: 2nd International Conference on Image, 2020

2019
Touch-Typing Detection Using Eyewear: Toward Realizing a New Interaction for Typing Applications.
Sensors, 2019

Automatic Electron Density Determination by Using a Convolutional Neural Network.
IEEE Access, 2019

Interaction to Support the Learning of Typing for Beginners on Physical Keyboard by Projection Mapping.
Proceedings of the ICIT 2019, 2019

Deep Metric Learning for Sensor-based Human Activity Recognition.
Proceedings of the ICIT 2019, 2019

Estimation of Sidewalk Surface Type with a Smartphone.
Proceedings of the ICIT 2019, 2019

Representation Learning by Convolutional Neural Network for Smartphone Sensor Based Activity Recognition.
Proceedings of the CIIS 2019: The 2nd International Conference on Computational Intelligence and Intelligent Systems, 2019

Finger Recognition Using a Wearable Device while Typing.
Proceedings of the CIIS 2019: The 2nd International Conference on Computational Intelligence and Intelligent Systems, 2019

2018
Estimation of Road Snow Accumulation Using Smartphones to Create Snow Cover Maps for Pedestrians.
Proceedings of the TENCON 2018, 2018

Touch-Typing Skills Estimation Using Eyewear.
Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2018

2017
Determining Smartphone's Placement Through Material Detection, Using Multiple Features Produced in Sound Echoes.
IEEE Access, 2017

2016
Determining a smartphone's placement by material detection using harmonics produced in sound echoes.
Proceedings of the 13th International Conference on Mobile and Ubiquitous Systems: Computing, 2016

2015
Analysis of Actual Smartphone Logs for Predicting the User's Routine Settings of Application Volume.
Proceedings of the 2015 IEEE International Conference on Systems, 2015

State magic: state estimation for Android smartphone.
Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers, 2015


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