Takashi Kuremoto

发表

Adaptive Control System Based on Self-Organizing Wavelet Neural Network with H8 Tracking Performance Compensator

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2013, 2013 IEEE International Conference on Systems, Man, and Cybernetics.

A hand shape instruction recognition and learning system using growing SOM with asymmetric neighborhood function

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2016, Neurocomputing.

Combination of genetic network programming and knapsack problem to support record clustering on distributed databases

Shingo Mabu, Masanao Obayashi, Takashi Kuremoto, 2016, Expert Syst. Appl..

Forecast chaotic time series data by DBNs

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2014, 2014 7th International Congress on Image and Signal Processing.

A Robust Cooperated Control Method with Reinforcement Learning and Adaptive H∞ Control

Kunikazu Kobayashi, Masanao Obayashi, Shogo Uchiyama, 2011 .

Handwriting character classification using Freeman’s olfactory KIII model

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2012, Artificial Life and Robotics.

An Improved Internal Model for Swarm Formation and Adaptive Swarm Behavior Acquisition

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2009, J. Circuits Syst. Comput..

Intelligent tracking control method of a target by group of agents with nonlinear dynamics

Kunikazu Kobayashi, Masanao Obayashi, Shogo Uchiyama, 2011, 2011 11th International Conference on Control, Automation and Systems.

A Meta-learning Method Based on Temporal Difference Error

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2009, ICONIP.

A Class Identification Method Using Freeman’s Olfactory KIII Model

Shingo Mabu, Masanao Obayashi, Takashi Kuremoto, 2016 .

A random-forests-based classifier using class association rules and its application to an intrusion detection system

Shingo Mabu, Masanao Obayashi, Takashi Kuremoto, 2016, Artificial Life and Robotics.

A Robust Control System Based on a Cerebellar Perceptron Improved Model

Kunikazu Kobayashi, Masanao Obayashi, Shogo Uchiyama, 2013 .

A Reinforcement Learning Method Based on Immune Network

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2007 .

An Optimization of Spatio-Spectral Filter Bank Design for EEG Classification

Shingo Mabu, Masanao Obayashi, Takashi Kuremoto, 2016 .

A Sentence Summarizer using Recurrent Neural Network and Attention-Based Encoder

Shingo Mabu, Masanao Obayashi, Takashi Kuremoto, 2017 .

A Robust Reinforcement Learning System Using Concept of Sliding Mode Control for Unknown Nonlinear Dynamical System

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2011 .

A variable size mechanism of distributed graph programs and its performance evaluation in agent control problems

Shingo Mabu, Kotaro Hirasawa, Masanao Obayashi, 2014, Expert Syst. Appl..

Optimization and verification for a robot control system based on learning petri net model

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2011 .

One dimensional ring type growing SOM with asymmetric neighborhood function and its application to a hand shape instruction learning system

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2014, 15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD).

A Reinforcement Learning System with Multi-Layered Fuzzy Neural Network

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2017 .

An Emotional Robot

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2015, IJCCI.

The Recollection Characteristics of Generalized MCNN Using Different Control Methods

Shingo Mabu, Shun Watanabe, Kunikazu Kobayashi, 2014, J. Robotics Netw. Artif. Life.

Deep Reinforcemnet Learning: A Promised Way to AI

Takashi Kuremoto, 2017 .

An Optimization of Spatio-Spectral Filter Bank Design for EEG Classification

Shingo Mabu, Masanao Obayashi, Takashi Kuremoto, 2016, J. Robotics Netw. Artif. Life.

A Novel Approach to Time Series Forecasting using Deep Learning and Linear Model

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2016 .

Leader-Follower Formation Control Using Cerebellar Perceptron Improved Model with Auto-structuring

Shingo Mabu, Masanao Obayashi, Takashi Kuremoto, 2016, 2016 IEEE Intl Conference on Computational Science and Engineering (CSE) and IEEE Intl Conference on Embedded and Ubiquitous Computing (EUC) and 15th Intl Symposium on Distributed Computing and Applications for Business Engineering (DCABES).

Lung Sound Classification Using Deep Neural Networks with Pre-training

Shoji Kido, Takashi Kuremoto, Ryosuke Wakamoto, 2020 .

A reinforcement learning method based on an immune network adapted to a semi-Markov decision process

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2008, Artificial Life and Robotics.

How an Adaptive Learning Rate Benefits Neuro-Fuzzy Reinforcement Learning Systems

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2014, ICSI.

Training Deep Neural Networks with Reinforcement Learning for Time Series Forecasting

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2019, Time Series Analysis - Data, Methods, and Applications.

One-D-R-A-G-SOM and its Application to a Hand Shape Instruction Learning System

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2014, Int. J. Networked Distributed Comput..

Investigating the Effects of Transfer Learning on ROI-based Classification of Chest CT Images: A Case Study on Diffuse Lung Diseases

Shingo Mabu, Shoji Kido, Takashi Kuremoto, 2020, J. Signal Process. Syst..

A method for analyzing the spatiotemporal changes of chaotic neural networks

Shun Watanabe, Kunikazu Kobayashi, Masanao Obayashi, 2013, Artificial Life and Robotics.

Enhancing EEG Signals Recognition Using ROC Curve

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2018, J. Robotics Netw. Artif. Life.

A Real-time Reinforcement Learning Control System with H^|^infin; Tracking Performance Compensator

Kunikazu Kobayashi, Masanao Obayashi, Shogo Uchiyama, 2012 .

An extended Q learning system with emotion state to make up an agent with individuality

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2015, 2015 7th International Joint Conference on Computational Intelligence (IJCCI).

A Model of Emotional Intelligent Agent for Cooperative Goal Exploration

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2013, ICIC.

The Dynamical Recollection of Interconnected Neural Networks Using Meta-heuristics

Shun Watanabe, Kunikazu Kobayashi, Masanao Obayashi, 2011 .

Robust Reinforcement Learning Control System with H ∞ tracking performance compensator

Kunikazu Kobayashi, Masanao Obayashi, Shogo Uchiyama, 2011 .

SemiSupervised Learning for Class Association Rule Mining Using Genetic Network Programming

Takuro Higuchi, Takashi Kuremoto, Shingo Mabu, 2020 .

A Meta-Parameter Learning Method in Reinforcement Learning Based on Temporal Difference Error

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2009 .

Actor-Critic Reinforcement Learning System with Time-Varying Parameters

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2003 .

Shapes of Non-monotonous Activation Functions in Chaotic Neural Network Associative Memory Model and Its Evaluation

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2006 .

A Control System Based on an Improved Model Auto-Fusion Cerebellar Perceptron and Its Application to the Consensus Problem

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2016 .

A Modified Recurrent Neural Network with Parametric Bias and its Application to Action Learning of a Humanoid Robot

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2014, ICIS 2014.

leader-following formation control with an adaptive linear and terminal sliding mode combined controller using auto-structuring fuzzy neural network

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2015 .

Time Series Forecasting Using Restricted Boltzmann Machine

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2012, ICIC.

Objective-based Reinforcement Learning System for Cooperative Behavior Acquisition

Koji Nakano, Kunikazu Kobayashi, Masanao Obayashi, 2010 .

Neural Forecasting Systems

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2008 .

An Action Selection Method Based on Estimation of Other's Intention in Time-Varying Multi-agent Environments

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2011, ICONIP.

Ensemble learning of rule-based evolutionary algorithm using multi layer perceptron for stock trading models

Shingo Mabu, Masanao Obayashi, Takashi Kuremoto, 2014, 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems (SCIS) and 15th International Symposium on Advanced Intelligent Systems (ISIS).

Disaster Area Detection from Synthetic Aperture Radar Images Using Convolutional Autoencoder and One-class SVM

Shingo Mabu, Takashi Kuremoto, Kohki Fujita, 2019, J. Robotics Netw. Artif. Life.

Forecasting Real Time Series Data using Deep Belief Net and Reinforcement Learning

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2017, J. Robotics Netw. Artif. Life.

A Neuro-fuzzy Learning System for Adaptive Swarm Behaviors Dealing with Continuous State Space

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2008, ICIC.

Indirect Adaptive Self-structuring Fuzzy Neural Network Control System

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2010 .

Autonomic Behaviors of Swarm Robots Driven by Emotion and Curiosity

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2010, LSMS/ICSEE.

Unsupervised and semi-supervised learning for efficient opacity annotation of diffuse lung diseases

Shingo Mabu, Yasushi Hirano, Shoji Kido, 2019, Other Conferences.

A Method of Feature Extraction for EEG Signals Recognition Using ROC Curve

Shingo Mabu, Masanao Obayashi, Takashi Kuremoto, 2017 .

Reinforcement Learning System with Time Varying Parameters Using Neural Networks

Hiroaki Kitano, Kunikazu Kobayashi, Masanao Obayashi, 2004 .

Mental Task Recognition by EEG Signals: A Novel Approach with ROC Analysis

Shingo Mabu, Masanao Obayashi, Takashi Kuremoto, 2017 .

Reinforcement Learning with Symbiotic Relationships for Multiagent Environments

Shingo Mabu, Masanao Obayashi, Takashi Kuremoto, 2015, J. Robotics Netw. Artif. Life.

On-line Rule Updating System Using Evolutionary Computation for Managing Distributed Database

Shingo Mabu, Masanao Obayashi, Takashi Kuremoto, 2015, J. Robotics Netw. Artif. Life.

Leader-Follower Adaptive Formation Control without Observation of Agent's Velocity Using Wavelet Neural Network

Shingo Mabu, Masanao Obayashi, Takashi Kuremoto, 2017, ICMLC.

Anomaly Detection of Disaster Areas from Satellite Images Using Convolutional Autoencoder and One-class SVM

Shingo Mabu, Takashi Kuremoto, Kohki Fujita, 2018 .

A Voice Instruction Learning System Using PL-T-SOM

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2009, 2009 2nd International Congress on Image and Signal Processing.

An Evolutionary Algorithm for Making Decision Graphs for Classification Problems

Shingo Mabu, Masanao Obayashi, Takashi Kuremoto, 2016, J. Robotics Netw. Artif. Life.

A variable size mechanism of distributed graph programs for creating agent behaviors

Shingo Mabu, Kotaro Hirasawa, Masanao Obayashi, 2013, 2013 IEEE Congress on Evolutionary Computation.

To extraction the feature of EEG signals for mental task recognition

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2015, 2015 54th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE).

MCNNとSOMを用いた動画像の記銘と動的想起;MCNNとSOMを用いた動画像の記銘と動的想起;Dynamical Recollection and Storage of Video Images via MCNN and SOM

Shingo Mabu, Shun Watanabe, Kunikazu Kobayashi, 2015 .

Shapes of nonmonotonic activation functions in a chaotic neural network associative memory model and its evaluation

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2008 .

Summarizing Articles into Sentences by Hierarchical Attention Model and RNN Language Model

Shingo Mabu, Takashi Kuremoto, Takuji Tsuruda, 2019, 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI).

A transient chaotic associative memory model with temporary stay function

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2011 .

A Robust Reinforcement Learning Control Design Method for Nonlinear System with Partially Unknown Structure

Kunikazu Kobayashi, Kazuhiro Nakano, Masanao Obayashi, 2010 .

A Control System Based on Auto-Fusion Cerebellar Perceptron Improved Model and Its Application to Consensus Problem

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2014 .

A Transient Chaotic Associative Memory Model with Temporary Stay Function

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2008 .

An Improved Internal Model of Autonomous Robots by a Psychological Approach

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2011, Cognitive Computation.

Opacity Labeling of Diffuse Lung Diseases in CT Images Using Unsupervised and Semi-supervised Learning

Shingo Mabu, Shoji Kido, Takashi Kuremoto, 2020 .

Dynamical recollection of interconnected neural networks using meta‐heuristics

Shun Watanabe, Kunikazu Kobayashi, Masanao Obayashi, 2012 .

Construction and Application of Learning Petri Net

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2012 .

A Functional Model of Limbic System of Brain

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2009, Brain Informatics.

Unsupervised class labeling of diffuse lung diseases using frequent attribute patterns

Shingo Mabu, Yasushi Hirano, Shoji Kido, 2016, International Journal of Computer Assisted Radiology and Surgery.

A Rule-Based Classification System Enhanced by Multi-Objective Genetic Algorithm

Shingo Mabu, Masanao Obayashi, Takashi Kuremoto, 2017, J. Robotics Netw. Artif. Life.

Implementation of genetic network programming and knapsack problem for record clustering on distributed database

Shingo Mabu, Masanao Obayashi, Takashi Kuremoto, 2014, 2014 Proceedings of the SICE Annual Conference (SICE).

The recollection characteristics of a generalized MCNN

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2013, The SICE Annual Conference 2013.

Behavior Selection Method of Robots Based on a Markovian Emotional Model

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2014 .

Multiple Action Sequence Learning and Automatic Generation for a Humanoid Robot Using RNNPB and Reinforcement Learning

Shingo Mabu, Koichi Hashiguchi, Kunikazu Kobayashi, 2012 .

A Decision Making System of Robots Introducing a Re-construction of Emotions Based on Their Own Experiences

Shingo Mabu, Masanao Obayashi, Shogo Watada, 2014, J. Robotics Netw. Artif. Life.

Robust Reinforcement Learning Control System with H∞ tracking performance compensator

Kunikazu Kobayashi, Masanao Obayashi, Shogo Uchiyama, 2011, 2011 11th International Conference on Control, Automation and Systems.

An Autonomous Mobile Robot with Functions of Action Learning, Memorizing, Recall and Identifying the Environment Using Gaussian Mixture Model

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2015, ICONIP.

A Neuro-fuzzy Network with Reinforcement Learning Algorithms for Swarm Learning

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2012 .

Landslide Classification from Synthetic Aperture Radar Images Using Convolutional Neural Network with Multichannel Information

Takashi Kuremoto, Shingo Mabu, Yoshiaki Nakayama, 2020, Journal of Signal Processing.

ELMAN TYPE RECURRENT NEURAL NETWORK WITH PARAMETRIC BIAS AND ITS APPLICATION TO MULTI-ACTION LEARNING OF ROBOT

Kunikazu Kobayashi, Takashi Kuremoto, Keita Morisaki, 2015 .

Nonlinear Prediction by Reinforcement Learning

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2005, ICIC.

A Self-Organized Fuzzy-Neuro Reinforcement Learning System for Continuous State Space for Autonomous Robots

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2008, 2008 International Conference on Computational Intelligence for Modelling Control & Automation.

Ensemble learning of rule-based evolutionary algorithm using multi-layer perceptron for supporting decisions in stock trading problems

Shingo Mabu, Masanao Obayashi, Takashi Kuremoto, 2015, Appl. Soft Comput..

Search Heuristics for the Optimization of DBN for Time Series Forecasting

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2020 .

RP-AG-SOM: A Growing Self-organizing Map with Assymetric Neighborhood Function and Variable Radius

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2016 .

A learning Fuzzy Petri net model

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2012 .

Neural Prediction of Chaotic Time Series Using Stochastic Gradient Ascent Algorithm

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2004 .

A tracking control method for a two wheeled robot using wavelet neural network-based sliding mode control

Shingo Mabu, Masanao Obayashi, Takashi Kuremoto, 2014 .

A Human-Machine Interaction System: A Voice Command Learning System Using PL-G-SOM

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2011, 2011 International Conference on Management and Service Science.

A dynamic associative memory system by adopting an amygdala model

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2009, Artificial Life and Robotics.

A Reinforcement Learning System Embedded Agent with Neural Network-Based Adaptive Hierarchical Memory Structure

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2011 .

Evolutionary Rule Based Clustering for Making Fuzzy Object Oriented Database Models

Shingo Mabu, Masanao Obayashi, Takashi Kuremoto, 2015, 2015 IIAI 4th International Congress on Advanced Applied Informatics.

Decentralized adaptive control using an affine plus self-organizing fuzzy neural network for Multi-Agent System consensus problem

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2013, 2013 International Conference on System Science and Engineering (ICSSE).

A Chaotic Model of Hippocampus-Neocortex

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2005, ICNC.

Evolutionary rule based clustering with fuzzy feature selection for high dimensional database

Shingo Mabu, Masanao Obayashi, Takashi Kuremoto, 2016 .

A Bayesian Local Linear Wavelet Neural Network

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2009, ICONIP.

A Visual System of Citrus Picking Robot Using Convolutional Neural Networks

Shingo Mabu, Takashi Kuremoto, Huang Ling, 2018, 2018 5th International Conference on Systems and Informatics (ICSAI).

Deep Belief Network Using Reinforcement Learning and Its Applications to Time Series Forecasting

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2016, ICONIP.

An intelligent control system construction using high-level time Petri net and Reinforcement Learning

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2010, ICCAS 2010.

A state predictor-based reinforcement learning system

Koji Nakano, Kunikazu Kobayashi, Masanao Obayashi, 2010 .

An Improved Reinforcement Learning System Using Affective Factors

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2013, Robotics.

Opacity annotation of diffuse lung diseases using deep convolutional neural network with multi-channel information

Shingo Mabu, Yasushi Hirano, Shoji Kido, 2018, Medical Imaging.

Cooperative Behavior Acquisition in Multi-agent Reinforcement Learning System Using Attention Degree

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2012, ICONIP.

A reinforcement learning system for swarm behaviors

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

A Local Linear Wavelet Neural Network Based on a Bayesian Design Method

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2009 .

Adaptive Swarm Behavior Acquisition Using a Neuro-Fuzzy Reinforcement Learning System

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2013 .

Time series forecasting using a deep belief network with restricted Boltzmann machines

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2014, Neurocomputing.

An emotional model embedded reinforcement learning system

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2012, 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

A State Predictor Based Reinforcement Learning System

Koji Nakano, Kunikazu Kobayashi, Masanao Obayashi, 2008 .

Intelligent agent construction using the attentive characteristic patterns of chaotic neural networks

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2010, Artificial Life and Robotics.

A Hand Shape Instruction Recognition and Learning System Using Growing SOM with Asymmetric Neighborhood Function

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2014, ICIC.

A Hippocampus-Neocortex Model for Chaotic Association

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2007, Trends in Neural Computation.

A gesture recognition system with retina-V1 model and one-pass dynamic programming

Shun Watanabe, Kunikazu Kobayashi, Masanao Obayashi, 2013, Neurocomputing.

Parameterless-Growing-SOM and Its Application to a Voice Instruction Learning System

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2010, J. Robotics.

Analysis of the effects of transfer learning on opacity classification of diffuse lung diseases using convolutional neural network

Shingo Mabu, Yasushi Hirano, Shoji Kido, 2019, Other Conferences.

A Gesture Recognition System Using One-Pass DP Method

Shun Watanabe, Kunikazu Kobayashi, Masanao Obayashi, 2011, ICIC.

A Hand Image Instruction Learning System Using Transient-SOM

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2007 .

An Improved Fuzzy Neural Network for Reinforcement Learning

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2019, ICBDR 2019.

Time Series Prediction Using DBN and ARIMA

Shingo Mabu, Kunikazu Kobayashi, Masanao Obayashi, 2015, 2015 International Conference on Computer Application Technologies.

Unsupervised Image Classification Using Multi-Autoencoder and K-means++

Shingo Mabu, Masanao Obayashi, Takashi Kuremoto, 2018, J. Robotics Netw. Artif. Life.

Enhanced decision making mechanism of rule-based genetic network programming for creating stock trading signals

Shingo Mabu, Kotaro Hirasawa, Masanao Obayashi, 2013, Expert Syst. Appl..

Adaptive swarm behavior acquisition by a neuro-fuzzy system and reinforcement learning algorithm

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2009, Int. J. Intell. Comput. Cybern..

Landslide Area Detection from Synthetic Aperture Radar Images Using Convolutional Adversarial Autoencoder and One-class SVM

Shingo Mabu, Takashi Kuremoto, Soichiro Hirata, 2021 .

Semi-supervised CycleGAN for domain transformation of chest CT images and its application to opacity classification of diffuse lung diseases

Shingo Mabu, Shoji Kido, Takashi Kuremoto, 2021, International Journal of Computer Assisted Radiology and Surgery.

Anomaly Detection Using Convolutional Adversarial Autoencoder and One-class SVM for Landslide Area Detection from Synthetic Aperture Radar Images

Shingo Mabu, Takashi Kuremoto, Soichiro Hirata, 2021, J. Robotics Netw. Artif. Life.

Instruction Learning Systems for Partner Robots

Takashi Kuremoto, 2013 .

A Reinforcement Learning System Based on State Space Construction Using Fuzzy ART A Reinforcement Learning System Based on State Space Construction Using Fuzzy ART

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2005 .

Forecasting Time Series by SOFNN with Reinforcement Learning

Kunikazu Kobayashi, Masanao Obayashi, Takashi Kuremoto, 2007 .