9 citations · 19 across the 7 of their papers we have counts for
22 papers
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…
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…
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…
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…
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…
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…