Real-Time Image Processing and Deep Learning 2020
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9781510635791, 9781510635807
Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

The combined denoising of images on the optical and thermal range onboard the UAV

2020 ◽  
Author(s):  
Evgeny A. Semenishchev ◽  
Viacheslav V. Voronin ◽  
Agaian Sos ◽  
Aleksandr Zelensky ◽  
Irina Tolstova
Keyword(s):  
Thermal Range

Computational aspects of deep learning models for detection of eye retina abnormalities

2020 ◽  
Author(s):  
Mohamed Akil ◽  
Yaroub Elloumi ◽  
Rostom Kachouri
Keyword(s):  
Deep Learning ◽  
Learning Models ◽  
Computational Aspects ◽  
Eye Retina

CNN to detect differences in cerebral cortical anatomy of left- and right- handers

2020 ◽  
Author(s):  
Lisa Meyer-Baese ◽  
Erik Roecher ◽  
Lucas Moesch ◽  
Danilo Bzdok ◽  
Klaus Mathiak
Keyword(s):  
Left And Right

A robust technique for real-time face verification with a generative network

2020 ◽  
Author(s):  
Ibrahim Batuhan Akkaya ◽  
Kaan Karaman
Keyword(s):  
Real Time ◽  
Face Verification

Coverless image steganography framework using distance local binary pattern and convolutional neural network

2020 ◽  
Author(s):  
Luis Alberto Sandoval-Bravo ◽  
Volodymyr I. Ponomaryov ◽  
Rogelio Reyes-Reyes ◽  
Clara Cruz-Ramos
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Local Binary Pattern ◽  
Image Steganography

Portable flow device using Fourier ptychography microscopy and deep learning for detection in biosignatures

2020 ◽  
Author(s):  
Thanh C. Nguyen ◽  
Shahid Aslam ◽  
Dina Bower ◽  
Jennifer Eigenbrode ◽  
Nicolas J. Gorius ◽  
...  
Keyword(s):  
Deep Learning ◽  
Flow Device

scholarly journals A deep learning-based smartphone app for real-time detection of five stages of diabetic retinopathy

2020 ◽  
Author(s):  
Sharmin Majumder ◽  
Yarub Elloumi ◽  
Mohamed Akil ◽  
Rostom Kachouri ◽  
Nasser Kehtarnavaz
Keyword(s):  
Diabetic Retinopathy ◽  
Deep Learning ◽  
Real Time ◽  
Smartphone App ◽  
Real Time Detection

No-reference image quality assessment based on residual neural networks (ResNets)

2020 ◽  
Author(s):  
Ravi S. Ravela ◽  
Mukul V. Shirvaikar ◽  
Christos Grecos
Keyword(s):  
Neural Networks ◽  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Reference Image
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