output
20172025
most citedAn Adaptive Learning Method of Deep Belief Network by Layer Generation Algorithm

33 citations

33 papers

cs.CV2025★ 8 cited

Automatic Extraction of Road Networks by using Teacher-Student Adaptive Structural Deep Belief Network and Its Application to Landslide Disaster

Shin Kamada, Takumi Ichimura

An adaptive structural learning method of Restricted Boltzmann Machine (RBM) and Deep Belief Network (DBN) has been developed as one of prominent deep learning models. The neuron g…

cs.NE2021★ 5 cited

An Embedded System for Image-based Crack Detection by using Fine-Tuning model of Adaptive Structural Learning of Deep Belief Network

Shin Kamada, Takumi Ichimura

Deep learning has been a successful model which can effectively represent several features of input space and remarkably improve image recognition performance on the deep architect…

cs.CV2021★ 1 cited

A Distillation Learning Model of Adaptive Structural Deep Belief Network for AffectNet: Facial Expression Image Database

Takumi Ichimura, Shin Kamada

Deep Learning has a hierarchical network architecture to represent the complicated feature of input patterns. We have developed the adaptive structure learning method of Deep Belie…

cs.CV2021★ 9 cited

An Adaptive Structural Learning of Deep Belief Network for Image-based Crack Detection in Concrete Structures Using SDNET2018

Shin Kamada, Takumi Ichimura, Takashi Iwasaki

We have developed an adaptive structural Deep Belief Network (Adaptive DBN) that finds an optimal network structure in a self-organizing manner during learning. The Adaptive DBN is…

cs.CV2021★ 2 cited

Automatic Extraction of Road Networks from Satellite Images by using Adaptive Structural Deep Belief Network

Shin Kamada, Takumi Ichimura

In our research, an adaptive structural learning method of Restricted Boltzmann Machine (RBM) and Deep Belief Network (DBN) has been developed as one of prominent deep learning mod…

cs.NE2019

Re-learning of Child Model for Misclassified data by using KL Divergence in AffectNet: A Database for Facial Expression

Takumi Ichimura, Shin Kamada

AffectNet contains more than 1,000,000 facial images which manually annotated for the presence of eight discrete facial expressions and the intensity of valence and arousal. Adapti…

cs.NE2019

A Video Recognition Method by using Adaptive Structural Learning of Long Short Term Memory based Deep Belief Network

Shin Kamada, Takumi Ichimura

Deep learning builds deep architectures such as multi-layered artificial neural networks to effectively represent multiple features of input patterns. The adaptive structural learn…

cs.NE2019★ 2 cited

An Object Detection by using Adaptive Structural Learning of Deep Belief Network

Shin Kamada, Takumi Ichimura

Deep learning forms a hierarchical network structure for representation of multiple input features. The adaptive structural learning method of Deep Belief Network (DBN) can realize…

cs.NE2018

Adaptive Structural Learning of Deep Belief Network for Medical Examination Data and Its Knowledge Extraction by using C4.5

Shin Kamada, Takumi Ichimura, Toshihide Harada

Deep Learning has a hierarchical network architecture to represent the complicated feature of input patterns. The adaptive structural learning method of Deep Belief Network (DBN) h…

cs.NE2018★ 8 cited

Knowledge Extracted from Recurrent Deep Belief Network for Real Time Deterministic Control

Shin Kamada, Takumi Ichimura

Recently, the market on deep learning including not only software but also hardware is developing rapidly. Big data is collected through IoT devices and the industry world will ana…

cs.NE2018★ 9 cited

Adaptive Learning Method of Recurrent Temporal Deep Belief Network to Analyze Time Series Data

Takumi Ichimura, Shin Kamada

Deep Learning has the hierarchical network architecture to represent the complicated features of input patterns. Such architecture is well known to represent higher learning capabi…

cs.NE2018★ 2 cited

Shortening Time Required for Adaptive Structural Learning Method of Deep Belief Network with Multi-Modal Data Arrangement

Shin Kamada, Takumi Ichimura

Recently, Deep Learning has been applied in the techniques of artificial intelligence. Especially, Deep Learning performed good results in the field of image recognition. Most new…

cs.IR2018★ 4 cited

A Recommendation System of Grants to Acquire External Funds

Shin Kamada, Takumi Ichimura, Takanobu Watanabe

The recommendation system of the competitive grants to university researchers by using the Grants-in-Aid for Scientific Research (KAKEN) keywords has been developed. The system can…

cs.MA2018

The Recommendation System to SNS Community for Tourists by Using Altruistic Behaviors

Takumi Ichimura, Takuya Uemoto, Shin Kamada

We have already developed the recommendation system of sightseeing information on SNS by using smartphone based user participatory sensing system. The system can post the attractiv…

cs.NE2018★ 33 cited

An Adaptive Learning Method of Deep Belief Network by Layer Generation Algorithm

Shin Kamada, Takumi Ichimura

Deep Belief Network (DBN) has a deep architecture that represents multiple features of input patterns hierarchically with the pre-trained Restricted Boltzmann Machines (RBM). A tra…

cs.NE2018★ 27 cited

An Adaptive Learning Method of Restricted Boltzmann Machine by Neuron Generation and Annihilation Algorithm

Shin Kamada, Takumi Ichimura

Restricted Boltzmann Machine (RBM) is a generative stochastic energy-based model of artificial neural network for unsupervised learning. Recently, RBM is well known to be a pre-tra…

cs.MA2018★ 4 cited

Emergence of Altruism Behavior for Multi Feeding Areas in Army Ant Social Evolutionary System

Takumi Ichimura, Takuya Uemoto, Akira Hara

Army ants perform the altruism that an ant sacrifices its own well-being for the benefit of another ants. Army ants build bridges using their own bodies along the path from a food…

cs.AI2018

An Estimation of Favorite Value in Emotion Generating Calculation by Fuzzy Petri Net

Takumi Ichimura, Kousuke Tanabe

Emotion Generating Calculations (EGC) method based on the Emotion Eliciting Condition Theory can decide whether an event arouses pleasure or not and quantify the degree under the e…

cs.HC2018★ 1 cited

Affective Recommendation System for Tourists by Using Emotion Generating Calculations

Takumi Ichimura, Issei Tachibana

An emotion orientated intelligent interface consists of Emotion Generating Calculations (EGC) and Mental State Transition Network (MSTN). We have developed the Android EGC applicat…

cs.IR2018★ 5 cited

Recommendation System of Grants-in-Aid for Researchers by using JSPS Keyword

Shin Kamada, Takumi Ichimura, Takanobu Watanabe

An acquisition of a research grant is important for the researchers to conduct a research. The university will build up the organization and reinforce the acquirement of external f…

cs.MA2018★ 2 cited

Analysis of the Social Community Based on the Network Growing Model in Open Source Software Community

Takumi Ichimura, Takuya Uemoto

The social community in open source software developers has a complex network structure. The network structure represents the relations between the project and the engineer in the…

cs.NE2018

A Generation Method of Immunological Memory in Clonal Selection Algorithm by using Restricted Boltzmann Machines

Shin Kamada, Takumi Ichimura

Recently, a high technique of image processing is required to extract the image features in real time. In our research, the tourist subject data are collected from the Mobile Phone…

cs.HC2018

An Adaptive Learning Method of Personality Trait Based Mood in Mental State Transition Network by Recurrent Neural Network

Takumi Ichimura, Kosuke Tanabe, Toshiyuki Yamashita

Mental State Transition Network (MSTN) is a basic concept of approximating to human psychological and mental responses. A stimulus calculated by Emotion Generating Calculations (EG…

cs.HC2018★ 3 cited

Tourist Navigation in Android Smartphone by using Emotion Generating Calculations and Mental State Transition Networks

Takumi Ichimura, Kosuke Tanabe, Issei Tachibana

Mental State Transition Network which consists of mental states connected to each other is a basic concept of approximating to human psychological and mental responses. It can repr…