Skip to search formSkip to main contentSkip to account menu
You are currently offline. Some features of the site may not work correctly.

Arsenazo-DBN

Known as: 3-((2-arsonophenyl)azo)-6-((2,6-dibromo-4-nitrophenyl)azo)-4,5-dihydroxy-2,7-naphthalenedisulfonic acid 
National Institutes of Health

Related topics

Related topics

2 relations

Broader (1)

Arsenazo III
analogs & derivatives

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2019
2019
Deep Belief Network Modeling for Automatic Liver Segmentation
The liver segmentation in CT scan images is a significant step toward the development of a quantitative biomarker for computer… 
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
2018
2018
A deep belief network with PLSR for nonlinear system modeling
2018
2018
Statistical monitoring of a wastewater treatment plant: A case study.
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
2017
2017
Investigation of activation functions in deep belief network
Deep Belief Network (DBN) is made up of stacked Restricted Boltzmann Machine layers associated with global weight fine-tuning for… 
  • figure 1
  • figure 2
  • figure 3
  • table I
  • figure 5
2017
2017
A hydraulic fault diagnosis method based on sliding-window spectrum feature and deep belief network
The vibration signal of hydraulic system contains abundant state information, so vibration testing technology is an effective way… 
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 6
2017
2017
Deep learning cognitive radar for micro UAS detection and classification
In this paper, we propose an intelligent cognitive radar system for detecting and classifying the micro unmanned aerial systems… 
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Review
2016
Review
2016
A brief survey on deep belief networks and introducing a new object oriented toolbox ( DeeBNet V 3 . 0 )
Nowadays, this is very popular to use the deep architectures in machine learning. Deep Belief Networks (DBNs) are deep… 
  • table 1
  • figure 1
  • figure 2
  • figure 3
  • figure 4
Highly Cited
2010
Highly Cited
2010
Convolutional Deep Belief Networks on CIFAR-10
We describe how to train a two-layer convolutional Deep Belief Network (DBN) on the 1.6 million tiny images dataset. When… 
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • table 1
Highly Cited
2007
Highly Cited
2007
Real-time Bayesian anomaly detection in streaming environmental data
[1] With large volumes of data arriving in near real time from environmental sensors, there is a need for automated detection of… 
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
2000
2000
Defining digital space through a visual language
approach of design at first glance. But there is just as in design the possibility to deal with larger constructs abstractly… 
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy, Terms of Service, and Dataset License
ACCEPT & CONTINUE