Automated Identification of Diabetic Retinopathy Using Artificial Neutral Network

2020 ◽  
Author(s):  
K. Dhivya ◽  
G. Premalatha ◽  
M. Kayathri
Keyword(s):  
Diabetic Retinopathy ◽  
Neutral Network ◽  
Automated Identification ◽  
Artificial Neutral Network

Automated identification and grading system of diabetic retinopathy using deep neural networks

2019 ◽  
Vol 175 ◽  
pp. 12-25 ◽  
Author(s):  
Wei Zhang ◽  
Jie Zhong ◽  
Shijun Yang ◽  
Zhentao Gao ◽  
Junjie Hu ◽  
...  
Keyword(s):  
Neural Networks ◽  
Diabetic Retinopathy ◽  
Deep Neural Networks ◽  
Grading System ◽  
Automated Identification

scholarly journals Bond Strength Assessment of Concrete-Corroded Rebar Interface Using Artificial Neutral Network

2020 ◽  
Vol 10 (14) ◽  
pp. 4724 ◽  
Author(s):  
Yi Wang ◽  
Zong Woo Geem ◽  
Kohei Nagai
Keyword(s):  
Bond Strength ◽  
Concrete Strength ◽  
Neutral Network ◽  
Machine Learning Techniques ◽  
Structural Safety ◽  
Ann Model ◽  
Back Propagation Algorithm ◽  
Strength Assessment ◽  
Artificial Neutral Network ◽  
Spacing Ratio

Bond strength assessment is important for reinforced concrete structures with rebar corrosion since the bond degradation can threaten the structural safety. In this study, to assess the bond strength in concrete-corroded rebar interface, one of the machine learning techniques, artificial neutral network (ANN), was utilized for the application. From existing literature, data related to the bond strength of concrete and corroded rebar were collected. The ANN model was applied to understand the factors on bond property degradation. For the input in the ANN model, the following factors were considered the relative bond strength: (1) corrosion level; (2) crack width; (3) cover-to-diameter ratio; and (4) concrete strength. For the cases with confinement (stirrups), (5) the diameter/stirrups spacing ratio was also considered. The assessment was conducted from input with single parameter to multiple parameters. The scaled feed-forward multi-layer perception ANN model with the error back-propagation algorithm of gradient descent and momentum was found to match the experimental and computed results. The correlation of each parameter to the bond strength degradation was clarified. In cases without confinement, the relative importance was (1) > (2) > (4) > (3), while it was (2) > (1) > (3) > (5) > (4) for the cases with confinement.

Daylight Perceptive Lighting and Artificial Neutral Network

2013 ◽  
Vol 816-817 ◽  
pp. 1077-1080
Author(s):  
Ying Ming Gao ◽  
Hao Li ◽  
Huan Yue Zhang ◽  
Nian Yu Zou ◽  
Jing Hui Zhang
Keyword(s):  
Data Fusion ◽  
Energy Saving ◽  
Energy Efficient ◽  
Neutral Network ◽  
Fusion Method ◽  
Artificial Neutral Network

Energy efficient character of daylight perceptive lighting was analyzed and a method to evaluate energy saving was present, according to the presentation the longer duration of indoor illumination being less than threshold is, the more energy is saved. With two sensors, a data fusion method was put forward to exclude interference and improve lighting comfort. With more than two sensors, data fusion based on neutral network was discussed.

Automated Identification of Diabetic Retinopathy Using Deep Learning

Ophthalmology ◽  
2017 ◽  
Vol 124 (7) ◽  
pp. 962-969 ◽  
Author(s):  
Rishab Gargeya ◽  
Theodore Leng
Keyword(s):  
Diabetic Retinopathy ◽  
Deep Learning ◽  
Automated Identification
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