Kazuhito Takenaka

Orcid: 0009-0001-0821-2724

According to our database1, Kazuhito Takenaka authored at least 24 papers between 2007 and 2024.

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

Timeline

Legend:

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Links

On csauthors.net:

Bibliography

2024
ODD and Behavior Based Scenario Generation for Automated Driving Systems.
IEEE Access, 2024

2020
Evaluating Mental State of Drivers in Automated Driving Using Heart Rate Variability towards Feasible Request-to-Intervene.
Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics, 2020

Real-Time Operational Driving Energy Management with Stochastic Vehicles Behavior Prediction.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2020

2018
Defect-Repairable Latent Feature Extraction of Driving Behavior via a Deep Sparse Autoencoder.
Sensors, 2018

Anomaly Detection of Roads from Driving Data Using a Statistical Discrepancy Measure.
Proceedings of the 21st International Conference on Intelligent Transportation Systems, 2018

2017
Visualization of Driving Behavior Based on Hidden Feature Extraction by Using Deep Learning.
IEEE Trans. Intell. Transp. Syst., 2017

Prediction of driving behavior based on sequence to sequence model with parametric bias.
Proceedings of the 20th IEEE International Conference on Intelligent Transportation Systems, 2017

Fast Inverse Reinforcement Learning with Interval Consistent Graph for Driving Behavior Prediction.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Sequence Prediction of Driving Behavior Using Double Articulation Analyzer.
IEEE Trans. Syst. Man Cybern. Syst., 2016

Determining Utterance Timing of a Driving Agent With Double Articulation Analyzer.
IEEE Trans. Intell. Transp. Syst., 2016

Driving word2vec: Distributed semantic vector representation for symbolized naturalistic driving data.
Proceedings of the 2016 IEEE Intelligent Vehicles Symposium, 2016

Reducing the negative effect of defective data on driving behavior segmentation via a deep sparse autoencoder.
Proceedings of the IEEE 5th Global Conference on Consumer Electronics, 2016

2015
Unsupervised Hierarchical Modeling of Driving Behavior and Prediction of Contextual Changing Points.
IEEE Trans. Intell. Transp. Syst., 2015

Automatic lane change extraction based on temporal patterns of symbolized driving behavioral data.
Proceedings of the 2015 IEEE Intelligent Vehicles Symposium, 2015

Essential feature extraction of driving behavior using a deep learning method.
Proceedings of the 2015 IEEE Intelligent Vehicles Symposium, 2015

Automatic generation of summarized driving video with music and captions.
Proceedings of the IECON 2015, 2015

2014
Prediction of Next Contextual Changing Point of Driving Behavior Using Unsupervised Bayesian Double Articulation Analyzer.
Proceedings of the 2014 IEEE Intelligent Vehicles Symposium Proceedings, 2014

Visualization of driving behavior using deep sparse autoencoder.
Proceedings of the 2014 IEEE Intelligent Vehicles Symposium Proceedings, 2014

Generating contextual description from driving behavioral data.
Proceedings of the 2014 IEEE Intelligent Vehicles Symposium Proceedings, 2014

2013
Unsupervised drive topic finding from driving behavioral data.
Proceedings of the 2013 IEEE Intelligent Vehicles Symposium (IV), 2013

Automatic drive annotation via multimodal latent topic model.
Proceedings of the 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2013

2012
Drive video summarization based on double articulation structure of driving behavior.
Proceedings of the 20th ACM Multimedia Conference, MM '12, Nara, Japan, October 29, 2012

Contextual scene segmentation of driving behavior based on double articulation analyzer.
Proceedings of the 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012

2007
Linear Discrimination Analysis of Monkey Behavior in an Alternative Free Choice Task.
J. Robotics Mechatronics, 2007


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