World's Best Scientists 2026 revealed!
Kazuya Takeda

Kazuya Takeda

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Computer Science
Japan
2025

D-Index & Metrics

Computer Science

D-Index
53
Citations
12181
World Ranking
4794
National Ranking
56

Research.com Recognitions

  • 2025 - Research.com Computer Science in Japan Leader Award
  • 2022 - Research.com Computer Science in Japan Leader Award

Overview

Kazuya Takeda is affiliated with Nagoya University in Japan and has contributed extensively to research primarily in the fields of Computer Science and Engineering. Their work spans numerous subfields, with a significant focus on Computer Vision and Pattern Recognition, Automotive Engineering, Artificial Intelligence, Signal Processing, and Economics and Econometrics.

The scientist's research covers several main topics including Autonomous Vehicle Technology and Safety, Sports Analytics and Performance, Anomaly Detection Techniques and Applications, Human-Automation Interaction and Safety, Sports Performance and Training, and Music and Audio Processing. This variety underscores a multidisciplinary approach to their studies.

Their recent papers include:

  • "A Survey of Autonomous Driving: Common Practices and Emerging Technologies" (2020), published in IEEE Access
  • "Perception and sensing for autonomous vehicles under adverse weather conditions: A survey" (2023), published in ISPRS Journal of Photogrammetry and Remote Sensing
  • "Performance Analysis of 10 Models of 3D LiDARs for Automated Driving" (2020), published in IEEE Access
  • "Extracting Human-Like Driving Behaviors From Expert Driver Data Using Deep Learning" (2020), published in IEEE Transactions on Vehicular Technology
  • "Distracted driving detection based on the fusion of deep learning and causal reasoning" (2022), published in Information Fusion

Kazuya Takeda collaborates frequently with a number of co-authors, including Alexander Carballo, Keisuke Fujii, Eijiro Takeuchi, and Tomoki Toda. These collaborations have contributed to a substantial body of work in their research areas.

Their publications appear mainly in venues such as arXiv (Cornell University), IEEE Access, Sensors, the 2022 IEEE Intelligent Vehicles Symposium (IV), and the Journal of Robotics and Mechatronics. The distribution of publications in these venues reflects a focus on automotive technology as well as broader engineering and computer science inquiries.

Best Publications

  • A Survey of Autonomous Driving: Common Practices and Emerging Technologies

    Ekim Yurtsever;Jacob Lambert;Alexander Carballo;Kazuya Takeda

  • An Open Approach to Autonomous Vehicles

    Shinpei Kato;Eijiro Takeuchi;Yoshio Ishiguro;Yoshiki Ninomiya

  • Driver Modeling Based on Driving Behavior and Its Evaluation in Driver Identification

    C. Miyajima;Y. Nishiwaki;K. Ozawa;T. Wakita

  • ATR Japanese speech database as a tool of speech recognition and synthesis

    Akira Kurematsu;Kazuya Takeda;Yoshinori Sagisaka;Shigeru Katagiri

  • JNAS: Japanese speech corpus for large vocabulary continuous speech recognition research

    Katunobu Itou;Mikio Yamamoto;Kazuya Takeda;Toshiyuki Takezawa

  • Speaker-Dependent WaveNet Vocoder.

    Akira Tamamori;Tomoki Hayashi;Kazuhiro Kobayashi;Kazuya Takeda

  • Evaluation of blind signal separation method using directivity pattern under reverberant conditions

    S. Kurita;H. Saruwatari;S. Kajita;K. Takeda

  • Blind source separation combining independent component analysis and beamforming

    Hiroshi Saruwatari;Satoshi Kurita;Kazuya Takeda;Fumitada Itakura

  • Analysis and recognition of whispered speech

    Taisuke Ito;Kazuya Takeda;Fumitada Itakura

  • Driver Identification Using Driving Behavior Signals

    Toshihiro Wakita;Koji Ozawa;Chiyomi Miyajima;Kei Igarashi

  • Espnet-TTS: Unified, Reproducible, and Integratable Open Source End-to-End Text-to-Speech Toolkit

    Tomoki Hayashi;Ryuichi Yamamoto;Katsuki Inoue;Takenori Yoshimura

  • Free software toolkit for Japanese large vocabulary continuous speech recognition

    Tatsuya Kawahara;Akinobu Lee;Tetsunori Kobayashi;Kazuya Takeda

  • A new phonetic tied-mixture model for efficient decoding

    A. Lee;T. Kawahara;K. Takeda;K. Shikano

  • Driving Profile Modeling and Recognition Based on Soft Computing Approach

    A. Wahab;Chai Quek;Chin Keong Tan;K. Takeda

  • Exploring multi-channel features for denoising-autoencoder-based speech enhancement

    Shoko Araki;Tomoki Hayashi;Marc Delcroix;Masakiyo Fujimoto

  • The Design of the Newspaper-Based Japanese Large Vocabulary Continuous Speech Recognition Corpus

    Katunobu Itou;Mikio Yamamoto;Kazuya Takeda;Toshiyuki Takezawa

  • Estimation of HRTFs on the horizontal plane using physical features

    Takanori Nishino;Naoya Inoue;Kazuya Takeda;Fumitada Itakura

  • Multipoint Measuring System for Video and Sound - 100-camera and microphone system

    T. Fujii;K. Mori;K. Takeda;K. Mase

  • An investigation of multi-speaker training for wavenet vocoder

    Tomoki Hayashi;Akira Tamamori;Kazuhiro Kobayashi;Kazuya Takeda

  • Duration-Controlled LSTM for Polyphonic Sound Event Detection

    Tomoki Hayashi;Shinji Watanabe;Tomoki Toda;Takaaki Hori

  • Driver Modeling Based on Driving Behavior and Its Evaluation in Driver

    Chiyomi Miyajima;Yoshihiro Nishiwaki;Koji Ozawa;Toshihiro Wakita

Frequent Co-Authors

Tomoki Toda
Tomoki Toda Nagoya University
Kiyohiro Shikano
Kiyohiro Shikano Nara Institute of Science and Technology
Satoshi Nakamura
Satoshi Nakamura Nara Institute of Science and Technology
Seiichi Yamamoto
Seiichi Yamamoto Doshisha University
Hiroshi Saruwatari
Hiroshi Saruwatari University of Tokyo
Shinji Watanabe
Shinji Watanabe Carnegie Mellon University
Tatsuya Kawahara
Tatsuya Kawahara Kyoto University
Gerhard Schmidt
Gerhard Schmidt Kiel University
Hirokazu Kameoka
Hirokazu Kameoka NTT (Japan)
Toshiaki Fujii
Toshiaki Fujii Nagoya University

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