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08/10/2023
Attention-based 3D CNN with Multi-layer Features for Alzheimer's Disease Diagnosis using Brain Images
Structural MRI and PET imaging play an important role in the diagnosis o...
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07/31/2023
Multi-modal Graph Neural Network for Early Diagnosis of Alzheimer's Disease from sMRI and PET Scans
In recent years, deep learning models have been applied to neuroimaging ...
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05/16/2022
Multiscale reconstruction of porous media based on multiple dictionaries learning
Digital modeling of the microstructure is important for studying the phy...
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03/03/2021
Real-World Single Image Super-Resolution: A Brief Review
Single image super-resolution (SISR), which aims to reconstruct a high-r...
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04/11/2019
FTGAN: A Fully-trained Generative Adversarial Networks for Text to Face Generation
As a sub-domain of text-to-image synthesis, text-to-face generation has ...
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04/04/2019
Accurate and Fast reconstruction of Porous Media from Extremely Limited Information Using Conditional Generative Adversarial Network
Porous media are ubiquitous in both nature and engineering applications,...
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03/25/2019
Capturing the symptoms of malicious code in electronic documents by file's entropy signal combined with Machine learning
Abstract-Email cyber-attacks based on malicious documents have become th...
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06/24/2018
CT-image Super Resolution Using 3D Convolutional Neural Network
Computed Tomography (CT) imaging technique is widely used in geological ...
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05/27/2018
DPW-SDNet: Dual Pixel-Wavelet Domain Deep CNNs for Soft Decoding of JPEG-Compressed Images
JPEG is one of the widely used lossy compression methods. JPEG-compresse...
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09/19/2017
CISRDCNN: Super-resolution of compressed images using deep convolutional neural networks
In recent years, much research has been conducted on image super-resolut...
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06/30/2015