A Two-Stage Convolutional Neural Network for Joint Demosaicking and Super-Resolution

2021 ◽  
pp. 1-1
Author(s):  
Kan Chang ◽  
Hengxin Li ◽  
Yufei Tan ◽  
Pak Lun Kevin Ding ◽  
Baoxin Li
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Super Resolution ◽  
Two Stage

scholarly journals A Real-time Driver Fatigue Detection Method Based on Two-Stage Convolutional Neural Network

2020 ◽  
Vol 53 (2) ◽  
pp. 15374-15379
Author(s):  
Hu He ◽  
Xiaoyong Zhang ◽  
Fu Jiang ◽  
Chenglong Wang ◽  
Yingze Yang ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Real Time ◽  
Detection Method ◽  
Driver Fatigue ◽  
Two Stage ◽  
Fatigue Detection

Learning depth super-resolution by using multi-scale convolutional neural network

2019 ◽  
Vol 36 (2) ◽  
pp. 1773-1783 ◽  
Author(s):  
Masoumeh Zareapoor ◽  
Pourya Shamsolmoali ◽  
Jie Yang
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Super Resolution ◽  
Multi Scale

scholarly journals Yamatani Activation: Edge Homogeneous Response Super Resolution Neural Network

2020 ◽  
Author(s):  
Takuma Yoshimura
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Dynamic Range ◽  
Super Resolution ◽  
Activation Function

In this research, I propose a two-variable activation function "Yamatani" that satisfies the first-degree homogeneity, and realize a super-resolution convolutional neural network that is independent of the dynamic range and symmetrical about the luminance inversion.

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