9 citations · 19 across the 7 of their papers we have counts for
14 papers · 1 filter
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…
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…
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…
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…
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…