“AI-empowered Panasonic”
An exciting journey starts here!

With more than 100 years of experiences in real-world appliances and applications,
and with our philosophy that what values most is making people's life better,
our challenges in real-world are now in the most exciting phase ever with AI.

RESEARCH AREA

In a wide range of fields not limited to those listed below,
we are working on research and development that utilizes cutting-edge AI/data analysis technology to contribute to society.

  • Image Recognition

  • Data Analysis

  • Robotics

  • Voice / Language

  • Biometric Data Analysis

  • AI / Iot Platform

PUBLICATIONS

  • IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS)2024

    A Contact Model based on Denoising Diffusion to Learn Variable Impedance Control for Contact-rich Manipulation

    Masashi Okada, Mayumi Komatsu and Tadahiro Taniguchi
    arXiv: https://arxiv.org/abs/2403.13221

  • The 41st International Conference on Machine Learning(ICML 2024)

    Split-Ensemble: Efficient OOD-aware Ensemble via Task and Model Splitting

    Anthony Chen, Huanrui Yang, Yulu Gan, Denis Gudovskiy, Zhen Dong, Haofan Wang, Tomoyuki Okuno, Yohei Nakata, Kurt Keutzer, Shanghang Zhang
    arXiv: https://arxiv.org/abs/2312.09148

  • The 41st International Conference on Machine Learning(ICML 2024)

    Hyperbolic Active Learning for Semantic Segmentation under Domain Shift

    Luca Franco, Paolo Mandica, Konstantinos Kallidromitis, Devin Guillory, Yu-Teng Li, Trevor Darrell, Fabio Galasso
    arXiv: https://arxiv.org/abs/2306.11180

  • ICML '24 Workshop on Advancing Neural Network Training (WANT): Computational Efficiency, Scalability, and Resource Optimization

    Fisher-aware Quantization for DETR Detectors with Critical-category Objectives

    Huanrui Yang, Yafeng Huang, Zhen Dong, Denis Gudovskiy, Tomoyuki Okuno, Yohei Nakata, Yuan Du, Kurt Keutzer, Shanghang Zhang
    arXiv: https://arxiv.org/abs/2407.03442

  • The Conference on Uncertainty in Artificial Intelligence(UAI2024)

    ContextFlow++: Generalist-Specialist Flow-based Generative Models with Mixed-Variable Context Encoding

    Denis Gudovskiy, Tomoyuki Okuno, Yohei Nakata
    arXiv: https://arxiv.org/abs/2406.00578

ABOUT

Innovate for better living, business and transportation
with AI technology to pursue our brand slogun “Live Your Best”