2 citations · 2 across the 3 of their papers we have counts for
27 papers
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…
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…