Faculty Profiles - TANAKA Yuichiro

Papers - TANAKA Yuichiro

Division display41 - 60 of about 71／ All the affair displays >>

In-material reservoir implementation of reservoir-based convolution Reviewed International journal

Tanaka Y., Usami Y., Tanaka H., Tamukoh H.

Proceedings - IEEE International Symposium on Circuits and Systems 2023-May 2023.05

Memory-Efficient Implementation of GMM-MRCoHOG for HumaRecognition Hardware Reviewed

Takemoto R., Nagamine Y., Yoshihiro K., Shibata M., Yamada H., Tanaka Y., Enokida S., Tamukoh H.

Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications 4 648 - 655 2023.02

Random network device fabricated using Ag<inf>2</inf>Se nanowires for data augmentation with binarized convolutional neural network Reviewed International journal

Kotooka T., Tanaka Y., Tamukoh H., Usami Y., Tanaka H.

Applied Physics Express 16 ( 1 ) 2023.01

Material computing based on electrochemical dynamics Reviewed

Yuki Usami, Yuichiro Tanaka, Takumi Kotooka, Hakaru Tamukoh, Hirofumi Tanaka

The 4th International Symposium on Neuromorphic AI Hardware 6 - 6 2022.12

Robust Trash Can Lid Opening System Reviewed

Kosei Isomoto, Yuga Yano, Yuichiro Tanaka, Hakaru Tamukoh

The 4th International Symposium on Neuromorphic AI Hardware 46 - 46 2022.12

Hardware-oriented Brain-inspired Model with Memory Accumulation and Recall Functions to Generate Actions of Home Service Robots Reviewed

Akinobu Mizutani, Ichiro Kawashima, Yuichiro Tanaka, Hakaru Tamukoh, Katsumi Tateno, Osamu Nomura, Takashi Morie

The 4th International Symposium on Neuromorphic AI Hardware 44 - 44 2022.12

Resorvoir-based neuron model to emulate cellular neural activity responding to odor in C. elegans Reviewed

Ryosuke Ishibashi, Takumi Nakamura, Noriko Sato, Takeshi Ishihara, Yuichiro Tanaka, Hakaru Tamukoh, Terumasa Tokunaga

The 4th International Symposium on Neuromorphic AI Hardware 42 - 42 2022.12

Deep Learning Method on Word Level American Sign Language Recognition from Video Reviewed

Arie Rachmad Syulistyo, Yuichiro Tanaka, Hakaru Tamukoh

The 4th International Symposium on Neuromorphic AI Hardware 28 - 28 2022.12

Reservoir-based 1D convolution Reviewed

Yuichiro Tanaka, Hakaru Tamukoh,

The 4th International Symposium on Neuromorphic AI Hardware 12 - 12 2022.12

Reservoir computing in the matter based on electrochemical dynamics Reviewed International journal

Usami Y, Tanaka Y, Tamukoh H, Matsumoto T, van der Wiel W, Tanaka H

16th International Conference on Nanostructured Materials (NANO2022) 2022.06

Reservoir-based convolution Reviewed International journal

Tanaka Yuichiro, Tamukoh Hakaru

Nonlinear Theory and Its Applications, IEICE ( The Institute of Electronics, Information and Communication Engineers ) 13 ( 2 ) 397 - 402 2022.04

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

<p>Reservoir computing (RC) has attracted attention and has been used in many applications because of its low training cost. Multiple studies using RC for image recognition have been proposed, and some have achieved accuracy rates of greater than 99% on the MNIST dataset. For the Fashion-MNIST and CIFAR-10 datasets, however, they have not yet achieved high accuracy. This study proposes a novel convolutional neural network based on RC that can be optimized by ridge regression rather than back-propagation. The reservoir-based network has multiple reservoirs with various leak rates to extract features with various spatial frequencies from the inputs. The experimental results show that the performance of the proposed model achieves higher accuracy rates in the mentioned datasets compared with those of other reservoir-based image recognition approaches.</p>

DOI： 10.1587/nolta.13.397

Kyutacar

Scopus

CiNii Research

Other Link： http://hdl.handle.net/10228/00009117

Hardware-oriented Algorithm for Human Detection using GMM-MRCoHOG Features Reviewed International journal

Takemoto R., Nagamine Y., Yoshihiro K., Shibata M., Yamada H., Tanaka Y., Enokida S., Tamukoh H.

Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications 4 749 - 757 2022.02

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

Daiju Kanaoka, Yuichiro Tanaka, Hakaru Tamukoh

17th International Conference on Computer Vision Theory and Applications (VISAPP2022) 5 359 - 365 2022.02

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

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Papers - TANAKA Yuichiro