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Takaya Kawakatsu
Takaya Kawakatsu
Preferred Networks, Inc.
Verified email at nii.ac.jp - Homepage
Title
Cited by
Cited by
Year
Deep Sensing Approach to Single-Sensor Vehicle Weighing System on Bridges
T Kawakatsu, K Aihara, A Takasu, J Adachi
IEEE Sensors Journal 19 (1), 243 - 256, 2019
302019
Traffic surveillance system for bridge vibration analysis
T Kawakatsu, A Kakitani, K Aihara, A Takasu, J Adachi
2017 IEEE International Conference on Information Reuse and Integration (IRI …, 2017
172017
Deep sensing approach to single-sensor bridge weighing in motion
T Kawakatsu, A Kinoshita, K Aihara, A Takasu, J Adachi
9th European Workshop on Structural Health Monitoring (EWSHM 2018), 2018
102018
Fully-Neural Approach to Heavy Vehicle Detection on Bridges Using a Single Strain Sensor
T Kawakatsu, K Aihara, A Takasu, J Adachi
2020 IEEE International Conference on Acoustics, Speech and Signal …, 2020
92020
Fully-Neural Approach to Vehicle Weighing and Strain Prediction on Bridges Using Wireless Accelerometers
T Kawakatsu, K Aihara, A Takasu, J Adachi, H Wang, T Nagayama
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and …, 2021
52021
Adversarial Media-Fusion Approach to Strain Prediction for Bridges
T Kawakatsu, K Aihara, A Takasu, J Adachi
8th International Conference on Pattern Recognition Applications and Methods, 2019
52019
Adversarial Spiral Learning Approach to Strain Analysis for Bridge Damage Detection
T Kawakatsu, A Kinoshita, K Aihara, A Takasu, J Adachi
International Conference on Big Data Analytics and Knowledge Discovery, 49-58, 2018
42018
Data-Driven Bridge Weigh-In-Motion
T Kawakatsu, K Aihara, A Takasu, T Nagayama, J Adachi
IEEE Sensors Journal 23 (15), 17064 - 17077, 2023
32023
Deep learning approach to modeling bridge dynamics using cameras and sensors
T Kawakatsu, K Aihara, A Takasu, J Adachi
10th International Conference on Bridge Maintenance, Safety and Management …, 2020
32020
A Data-Driven Approach for Bridge Weigh-in-Motion from Impact Acceleration Responses at Bridge Joints
H Wang, T Nagayama, T Kawakatsu, A Takasu
Structural Control and Health Monitoring 2023, 2023
12023
Divide-and-Conquer Parallelism for Learning Mixture Models
T Kawakatsu, A Kinoshita, A Takasu, J Adachi
Transactions on Large-Scale Data-and Knowledge-Centered Systems XXVIII …, 2016
12016
Highly efficient parallel framework: a divide-and-conquer approach
T Kawakatsu, A Kinoshita, A Takasu, J Adachi
Database and Expert Systems Applications: 26th International Conference …, 2015
12015
Multi-Cell Decoder and Mutual Learning for Table Structure and Character Recognition
T Kawakatsu
International Conference on Document Analysis and Recognition (ICDAR), 2024
2024
Estimation of Highway Bridges' Deflection from Acceleration Measurement by Using a Machine Learning Approach
AE Mustafa, T Nagayama, T Kawakatsu, A Takasu, O Sanada, ...
77th Annual Conference of the Japan Society of Civil Engineers (JSCE), 2022
2022
Deflection Estimation of Highway Bridges Based on Acceleration Measurement Using a Machine Learning Approach
AE Mustafa, T Nagayama, T Kawakatsu, A Takasu, O Sanada, ...
8th World Conference on Structural Control and Monitoring (WCSCM), 2022
2022
Vehicle Monitoring on Bridges Using Deep Learning
A Takasu, T Kawakatsu, K Aihara, J Adachi
計測と制御 60 (11), 775-779, 2021
2021
A data management platform for efficient monitoring of infrastructures
K Aihara, A Takasu, T Kawakatsu, A Kinoshita, J Adachi
10th International Conference on Bridge Maintenance, Safety and Management …, 2020
2020
Deep Sensing Approach to Media-Fusion Analysis for Modeling Bridge Dynamics
T Kawakatsu
Department of Information and Communication Engineering, The University of Tokyo, 2020
2020
Deep Sensing Approach to Vehicle Detection from Bridge Vibration
T Kawakatsu, A Kinoshita, K Aihara, A Takasu, J Adachi
12th International Workshop on Information Search, Integration, and …, 2018
2018
Efficient Divide-and-Conquer Parallelism in Machine Learning for Mixture Models
T Kawakatsu
Department of Information and Communication Engineering, The University of Tokyo, 2016
2016
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