Deep image retrieval of large-scale vessels images based on BoW model
Sign Up to like & getrecommendations! Published in 2019 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-019-7725-y
Abstract: This paper focuses on the vessel image retrieval from massive data, whose goal is to identify relevant records quickly and accurately when new images are given. Noteworthy, it is necessary to find features with high… read more here.
Keywords: large scale; retrieval large; vessels images; image ... See more keywords
Masked Joint Bilateral Filtering via Deep Image Prior for Digital X-Ray Image Denoising
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal of Biomedical and Health Informatics"
DOI: 10.1109/jbhi.2022.3179652
Abstract: Medical image denoising faces great challenges. Although deep learning methods have shown great potential, their efficiency is severely affected by millions of trainable parameters. The non-linearity of neural networks also makes them difficult to be… read more here.
Keywords: filtering; image denoising; joint bilateral; deep image ... See more keywords
Progressive Deep Image Compression for Hybrid Contexts of Image Classification and Reconstruction
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Journal on Selected Areas in Communications"
DOI: 10.1109/jsac.2022.3221998
Abstract: Progressive deep image compression (DIC) with hybrid contexts is an under-investigated problem that aims to jointly maximize the utility of a compressed image for multiple contexts or tasks under variable rates. In this paper, we… read more here.
Keywords: image compression; progressive deep; classification; deep image ... See more keywords
Hyperspectral Mixed Noise Removal via Spatial-Spectral Constrained Unsupervised Deep Image Prior
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2021.3111404
Abstract: Recently, deep learning-based methods are proposed for hyperspectral images (HSIs) denoising. Among them, unsupervised methods such as deep image prior (DIP)-based methods have received much attention because these methods do not require any training data.… read more here.
Keywords: based methods; image prior; deep image; dip based ... See more keywords
Unsupervised Hyperspectral Denoising Based on Deep Image Prior and Least Favorable Distribution
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2022.3187722
Abstract: This article considers the inverse problem under hyperspectral images (HSIs) denoising framework. Recently, it has been shown that deep learning is a promising approach to image denoising. However, deep learning to be effective usually needs… read more here.
Keywords: favorable distribution; least favorable; deep image; image prior ... See more keywords
UnDIP: Hyperspectral Unmixing Using Deep Image Prior
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2021.3067802
Abstract: In this article, we introduce a deep learning-based technique for the linear hyperspectral unmixing problem. The proposed method contains two main steps. First, the endmembers are extracted using a geometric endmember extraction method, i.e., a… read more here.
Keywords: hyperspectral unmixing; image prior; deep image; using deep ... See more keywords
A Robust 3-D Reconstruction Approach Based on Correspondence Retrieval Using Deep Image Prior
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2023.3267526
Abstract: In stereo phase-shifting profilometry (PSP), the performance of stereo matching algorithm directly determines the result of final reconstruction. Deep learning has been introduced in correspondence retrieval owing to its superiority in solving inverse problems. However,… read more here.
Keywords: correspondence retrieval; reconstruction; image; deep image ... See more keywords
Variational Deep Image Restoration
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2022.3183835
Abstract: This paper presents a new variational inference framework for image restoration and a convolutional neural network (CNN) structure that can solve the restoration problems described by the proposed framework. Earlier CNN-based image restoration methods primarily… read more here.
Keywords: restoration; cnn; image restoration; variational deep ... See more keywords
Weakly Supervised Complets Ranking for Deep Image Quality Modeling
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2019.2962548
Abstract: Despite the competitive prediction performance, recent deep image quality models suffer from the following limitations. First, it is deficiently effective to interpret and quantify the region-level quality, which contributes to global features during deep architecture… read more here.
Keywords: quality; quality modeling; deep image; image ... See more keywords
DeepEIT: Deep Image Prior Enabled Electrical Impedance Tomography.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE transactions on pattern analysis and machine intelligence"
DOI: 10.1109/tpami.2023.3240565
Abstract: Neural networks (NNs) have been widely applied in tomographic imaging through data-driven training and image processing. One of the main challenges in using NNs in real medical imaging is the requirement of massive amounts of… read more here.
Keywords: electrical impedance; impedance tomography; deep image; image prior ... See more keywords
Blind Poissonian Image Deblurring Regularized by a Denoiser Constraint and Deep Image Prior
Sign Up to like & getrecommendations! Published in 2020 at "Mathematical Problems in Engineering"
DOI: 10.1155/2020/9483521
Abstract: The denoising and deblurring of Poisson images are opposite inverse problems. Single image deblurring methods are sensitive to image noise. A single noise filter can effectively remove noise in advance, but it also damages blurred… read more here.
Keywords: image prior; image; deep image; image deblurring ... See more keywords