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ORCIDTatsuhito Hasegawa
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2020 – today
- 2024
[j11]Zhao Zhongkai
, Koki Takenaka, Tatsuhito Hasegawa:
Expanding the Horizons of 1-D Tasks: Leveraging 2-D Convolutional Neural Networks Pretrained by ImageNet. IEEE Internet Things J. 11(19): 30978-30995 (2024)- 2023
- [j10]Tatsuhito Hasegawa, Kazuma Kondo:
Easy Ensemble: Simple Deep Ensemble Learning for Sensor-Based Human Activity Recognition. IEEE Internet Things J. 10(6, March 15): 5506-5518 (2023) - [j9]Hyuga Tsutsumi, Kei Kondo, Koki Takenaka, Tatsuhito Hasegawa:
Sensor-Based Activity Recognition Using Frequency Band Enhancement Filters and Model Ensembles. Sensors 23(3): 1465 (2023) - [j8]Koki Takenaka, Kei Kondo, Tatsuhito Hasegawa:
Segment-Based Unsupervised Learning Method in Sensor-Based Human Activity Recognition. Sensors 23(20): 8449 (2023) - 2022
- [j7]Zhongkai Zhao, Satoshi Kobayashi, Kazuma Kondo, Tatsuhito Hasegawa, Makoto Koshino:
A Comparative Study: Toward an Effective Convolutional Neural Network Architecture for Sensor-Based Human Activity Recognition. IEEE Access 10: 20547-20558 (2022) - [c15]Koki Takenaka, Tatsuhito Hasegawa:
Unsupervised Representation Learning Method In Sensor Based Human Activity Recognition. ICMLC 2022: 25-30 - [c14]Zhongkai Zhao, Tatsuhito Hasegawa:
Domain-Robust Pre-Training Method for the Sensor-Based Human Activity Recognition. ICMLC 2022: 67-71 - [i3]Tatsuhito Hasegawa, Kazuma Kondo:
Easy Ensemble: Simple Deep Ensemble Learning for Sensor-Based Human Activity Recognition. CoRR abs/2203.04153 (2022) - 2021
- [j6]Tatsuhito Hasegawa:
Octave Mix: Data Augmentation Using Frequency Decomposition for Activity Recognition. IEEE Access 9: 53679-53686 (2021) - [j5]Kazuma Kondo, Tatsuhito Hasegawa:
Sensor-Based Human Activity Recognition Using Adaptive Class Hierarchy. Sensors 21(22): 7743 (2021) - [j4]Satoshi Kobayashi, Tatsuhito Hasegawa:
Detection of Motion on a Trampoline with a Smartwatch. Sensors 21(24): 8413 (2021) - [c13]Mahiro Imabeppu, Tatsuhito Hasegawa:
Effects of Different Activities on Learning Efficiency of m-Learning Users. TALE 2021: 1-8 - [i2]Tatsuhito Hasegawa:
Smartphone Sensor-based Human Activity Recognition Robust to Different Sampling Rates. CoRR abs/2101.00812 (2021) - [i1]Tatsuhito Hasegawa:
Octave Mix: Data augmentation using frequency decomposition for activity recognition. CoRR abs/2101.02882 (2021) - 2020
- [c12]Hanano Masuda, Takahiro Jukei, Tatsuhito Hasegawa:
Fish Species Identification Using a CNN-based Multimodal Learning Method. IVSP 2020: 15-19 - [c11]Kazuma Kondo, Tatsuhito Hasegawa:
CNN-based Criteria for Classifying Artists by Illustration Style. IVSP 2020: 93-98
2010 – 2019
- 2019
- [j3]Tatsuhito Hasegawa, Shoya Matsuda, Atsushi Kumamoto, Fuminori Tsuchiya, Yoshiya Kasahara, Yoshizumi Miyoshi, Yasumasa Kasaba, Ayako Matsuoka, Iku Shinohara:
Automatic Electron Density Determination by Using a Convolutional Neural Network. IEEE Access 7: 163384-163394 (2019) - [j2]Tatsuhito Hasegawa, Tatsuya Hatakenaka:
Touch-Typing Detection Using Eyewear: Toward Realizing a New Interaction for Typing Applications. Sensors 19(9): 2022 (2019) - [c10]Tatsuhito Hasegawa, Makoto Koshino:
Representation Learning by Convolutional Neural Network for Smartphone Sensor Based Activity Recognition. CIIS 2019: 99-104 - [c9]Daisuke Hamazaki, Tatsuhito Hasegawa:
Finger Recognition Using a Wearable Device while Typing. CIIS 2019: 105-110 - [c8]Makoto Mizuno, Tatsuhito Hasegawa:
Deep Metric Learning for Sensor-based Human Activity Recognition. ICIT 2019: 18-23 - [c7]Satoshi Kobayashi, Ren Katsurada, Tatsuhito Hasegawa:
Estimation of Sidewalk Surface Type with a Smartphone. ICIT 2019: 497-502 - [c6]Chikako Sono, Tatsuhito Hasegawa:
Interaction to Support the Learning of Typing for Beginners on Physical Keyboard by Projection Mapping. ICIT 2019: 565-569 - 2018
- [c5]Tatsuhito Hasegawa, Tatsuya Hatakenaka:
Touch-Typing Skills Estimation Using Eyewear. SMC 2018: 3833-3837 - [c4]Ren Katsurada, Tatsuhito Hasegawa:
Estimation of Road Snow Accumulation Using Smartphones to Create Snow Cover Maps for Pedestrians. TENCON 2018: 599-604 - 2017
- [j1]Tatsuhito Hasegawa, Satoshi Hirahashi, Makoto Koshino:
Determining Smartphone's Placement Through Material Detection, Using Multiple Features Produced in Sound Echoes. IEEE Access 5: 5331-5339 (2017) - 2016
- [c3]Tatsuhito Hasegawa, Satoshi Hirahashi, Makoto Koshino:
Determining a smartphone's placement by material detection using harmonics produced in sound echoes. MobiQuitous 2016: 246-253 - 2015
- [c2]Tatsuhito Hasegawa, Makoto Koshino, Satoshi Hirahashi, Haruhiko Kimura:
State magic: state estimation for Android smartphone. UbiComp/ISWC Adjunct 2015: 81-84 - [c1]Tatsuhito Hasegawa, Makoto Koshino, Haruhiko Kimura:
Analysis of Actual Smartphone Logs for Predicting the User's Routine Settings of Application Volume. SMC 2015: 2654-2659
Coauthor Index
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