Faculty Profiles - TANAKA Yuichiro

Papers - TANAKA Yuichiro

Division display41 - 58 of about 58／ All the affair displays >>

Applying Center Loss to Multidimensional Feature Space in Deep Neural Networks for Open-set Recognition Reviewed

Kanaoka D., Tanaka Y., Tamukoh H.

Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications 5 359 - 365 2022.01

Reservoir-based Convolutional Neural Network Reviewed International journal

Yuichiro Tanaka, Hakaru Tamukoh

The 2021 NonLinear Science Workshop NLSW-34 2021.12

Brain-inspired neural network navigation system with hippocampus, prefrontal cortex, and amygdala functions Reviewed

Mizutani A., Tanaka Y., Tamukoh H., Katori Y., Tateno K., Morie T.

ISPACS 2021 - International Symposium on Intelligent Signal Processing and Communication Systems: 5G Dream to Reality, Proceeding 2021.01

Open Set Recognition Using the Feature Space of Deep Neural Networks Reviewed International journal

Kanaoka D., Tanaka Y., Tamukoh H.

ISPACS 2021 - International Symposium on Intelligent Signal Processing and Communication Systems: 5G Dream to Reality, Proceeding 2021.01

In-Materio Reservoir Computing in a Sulfonated Polyaniline Network Reviewed

Usami Y., van de Ven B., Mathew D.G., Chen T., Kotooka T., Kawashima Y., Tanaka Y., Otsuka Y., Ohoyama H., Tamukoh H., Tanaka H., van der Wiel W.G., Matsumoto T.

Advanced Materials 33 ( 48 ) 2021.01

A Brain-Inspired Artificial Intelligence Model of Hippocampus, Amygdala, and Prefrontal Cortex on Home Service Robots Reviewed International journal

Tanaka Yuichiro, Tamukoh Hakaru, Tateno Katsumi, Katori Yuichi, Morie Takashi

IEICE Proceeding Series ( The Institute of Electronics, Information and Communication Engineers ) 74 138 - 141 2020.11

Authorship：Lead author,　Corresponding author Language：English Publishing type：Research paper (scientific journal)

We propose a brain-inspired artificial intelligence model that acquires local knowledge from a small number of human-robot interactions, and uses this knowledge for future prediction. We focus on areas of the brain: the hippocampus, the amygdala, and the prefrontal cortex, thereby providing an internal representation of place and time, a value judgment, and a prediction. By integrating these functions, our model achieves local knowledge acquisition and future prediction. The proposed model is evaluated in a task for home service robots. In the experiment, the model learns local time-series events from a small number of interactions, and predicts the future events.

DOI： 10.34385/proc.74.a4l-c-4

CiNii Research

Other Link： https://kyutech.repo.nii.ac.jp/records/2001270

A Reservoir Based Q-Learning Model for Autonomous Mobile Robots Reviewed International journal

Inada Masafumi, Tanaka Yuichiro, Tamukoh Hakaru, Tateno Katsumi, Morie Takashi, Katori Yuichi

IEICE Proceeding Series ( The Institute of Electronics, Information and Communication Engineers ) 74 213 - 216 2020.11

Language：English Publishing type：Research paper (scientific journal)

We propose a robot navigation system using reinforcement learning and reservoir computing. Reservoir computing is a framework for the processing of complex time series based on a recurrent neural network (RNN). The proposed system is trained by reinforcement learning, which is a framework that performs trial and error based on the rewards given by the environment. The trained network generates motor commands reflecting on action values obtained by the reinforcement learning and operates the autonomous mobile robot.

DOI： 10.34385/proc.74.b3l-b-5

CiNii Research

Other Link： https://kyutech.repo.nii.ac.jp/records/2001273

An Amygdala-Inspired Classical Conditioning Model Implemented on an FPGA for Home Service Robots Reviewed

Tanaka Y., Morie T., Tamukoh H.

IEEE Access 8 212066 - 212078 2020.11

Object Recognition Using Flexible Tactile Sensor Reviewed

Shoshi Tokuno, Yuichiro Tanaka, Takumi Kawasetsu, Koh Hosoda, Hakaru Tamukoh

Asia Pacific Conference on Robot IoT System Development and Platform 2020 2020.11

Prediction of Sensory Information and Generation of Motor Commands for Autonomous Mobile Robots using Reservoir Computing Reviewed

Masafumi Inada, Yuichiro Tanaka, Hakaru Tamukoh, Katsumi Tateno, Takashi Morie, Yuichi Katori

2019 International Symposium on Nonlinear Theory and Its Applications 333 - 336 2019.12

Research and Development of Home Service Robots Aiming for Social Implementation

ONO Tomohiro, SAKATA Takuma, YOSHII Takumi, KAMIMURA Daichi, KANAMARU Kazuki, NAKAMURA Kentaro, NISHIMURA Yuta, MORIE Takashi, TAMUKOH Hakaru, HORI Sansei, ISHIDA Yutaro, TANAKA Yuichiro, YOSHIMOTO Yuma, ABE Yushi, MUTO Fuyuki, KABASHIMA Kohei, FUKUYADO Masashi

The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) ( The Japan Society of Mechanical Engineers ) 2019 ( 0 ) 1P2 - I02 2019.06

Language：Japanese Publishing type：Research paper (conference, symposium, etc.)

<p>Home service robots have begun attracting attention due to decreasing birthrate and increasing aging population. We,"Hibikino-Musashi@Home"team, develop home service robots, and participate international competitions; RoboCup@Home and World Robot Challenge (WRC), which are established to realize that robots will work and live with people in domestic environments. In this paper, we introduce our robots and technologies, especially an object recognition and manipulation system. We use You Only Look Once (YOLO) for object recognition. To train YOLO, a big dataset which is difficult to prepare in a short term is required. For this, we develop an automatic annotation system for YOLO which can generate 1.7 million training data, and we can complete training of YOLO in a day. To grasp objects, estimation of object orientations is required. Our system can detect the orientations by processing point clouds of objects. By using the system, we obtained about 30% of scores in Tidy Up Task in the WRC.</p>

DOI： 10.1299/jsmermd.2019.1P2-I02

CiNii Article

CiNii Research

Other Link： https://ci.nii.ac.jp/naid/130007774525

Hardware implementation of brain-inspired amygdala model Reviewed International journal

Tanaka Y., Tamukoh H.

Proceedings - IEEE International Symposium on Circuits and Systems 2019-May 2019.01

Live demonstration: Hardware implementation of brain-inspired amygdala model Reviewed International journal

Tanaka Y., Tamukoh H.

Proceedings - IEEE International Symposium on Circuits and Systems 2019-May 2019.01

Live demonstration: A VLSI implementation of time-domain analog weighted-sum calculation model for intelligent processing on robots Reviewed International journal

Yamaguchi M., Iwamoto G., Abe Y., Tanaka Y., Ishida Y., Tamukoh H., Morie T.

Proceedings - IEEE International Symposium on Circuits and Systems 2019-May 2019.01

Application of digital hardware of deep self-organizing map network Reviewed

Yuichiro Tanaka, Hakaru Tamukoh

Asia Pacific Conference on Robot IoT System Development and Platform 2018 2018.10

Research and development of service robots by competition activities

YOSHIMOTO Yuma, IWAMOTO Gouki, HASHIMOTO Kouhei, MORIE Takashi, TAMUKOH Hakaru, HORI Sansei, ISHIDA Yutaro, KIYAMA Yuta, KURODA Yuki, TANAKA Yuichiro, HISANO Masataka, FUJITA Hiroto, ARATANI Yoshiya

The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) ( The Japan Society of Mechanical Engineers ) 2018 ( 0 ) 2P2 - E02 2018.06

Language：Japanese Publishing type：Research paper (conference, symposium, etc.)

<p>In real world applications of home service robots, they are required to be able to perform housekeeping or other tasks. "RoboCup@Home" is a competition for benchmarking home service robots. It includes tests to service robots for real world implementation. These tests require the combination of intelligent functions such as object detection and voice recognition. We have developed a home service robot "Exi@" and evaluated its performance by participating in RoboCup@Home. This paper describes real world implementation of robots and RoboCup@Home. The functions embedded in Exi@ and a task "Restaurant" are also explained.</p>

DOI： 10.1299/jsmermd.2018.2P2-E02

CiNii Article

CiNii Research

Other Link： https://ci.nii.ac.jp/naid/130007552042

Hardware implementation of deep self-organizing map networks Reviewed

Tanaka Y., Tamukoh H.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 10613 LNCS 439 - 441 2017.09

Hardware-Oriented Algorithm for Deep Neural Networks Composed of Self-Organizing Maps Reviewed

Yuichiro Tanaka, Hakaru Tamukoh

Proceedings of International Workshop on Smart Info-Media Systems in Asia 116 - 121 2016.09

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Papers - TANAKA Yuichiro