A dictionary‐based graph‐cut algorithm for MRI reconstruction
Sign Up to like & getrecommendations! Published in 2020 at "NMR in Biomedicine"
DOI: 10.1002/nbm.4344
Abstract: Compressive sensing (CS)‐based image reconstruction methods have proposed random undersampling schemes that produce incoherent, noise‐like aliasing artifacts, which are easier to remove. The denoising process is critically assisted by imposing sparsity‐enforcing priors. Sparsity is known… read more here.
Keywords: reconstruction; based graph; graph cut; cut algorithm ... See more keywords
Comparative study of distance-based graph invariants
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Applied Mathematics and Computing"
DOI: 10.1007/s12190-020-01363-2
Abstract: The investigation on relationships between various graph invariants has received much attention over the past few decades, and some of these research are associated with Graffiti conjectures (Fajtlowicz and Waller in Congr Numer 60:187–197, 1987)… read more here.
Keywords: based graph; least three; distance based; distance ... See more keywords
Recognition of building group patterns in topographic maps based on graph partitioning and random forest
Sign Up to like & getrecommendations! Published in 2018 at "Isprs Journal of Photogrammetry and Remote Sensing"
DOI: 10.1016/j.isprsjprs.2017.12.001
Abstract: Abstract Recognition of building group patterns (i.e., the arrangement and form exhibited by a collection of buildings at a given mapping scale) is important to the understanding and modeling of geographic space and is hence… read more here.
Keywords: group patterns; building group; based graph; recognition building ... See more keywords
Short-term traffic speed forecasting based on graph attention temporal convolutional networks
Sign Up to like & getrecommendations! Published in 2020 at "Neurocomputing"
DOI: 10.1016/j.neucom.2020.06.001
Abstract: Abstract Accurate and timely traffic forecasting is significant for intelligent transportation management. However, existing approaches model the temporal and spatial features of traffic flow inadequately. To address these limitations, a novel deep learning traffic forecasting… read more here.
Keywords: traffic; based graph; temporal convolutional; attention temporal ... See more keywords
RGN: Residue-Based Graph Attention and Convolutional Network for Protein-Protein Interaction Site Prediction
Sign Up to like & getrecommendations! Published in 2022 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.2c01092
Abstract: The prediction of a protein-protein interaction site (PPI site) plays a very important role in the biochemical process, and lots of computational methods have been proposed in the past. However, the majority of the past… read more here.
Keywords: network; site; prediction; residue based ... See more keywords
Analysis of E-mail Account Probing Attack Based on Graph Mining
Sign Up to like & getrecommendations! Published in 2020 at "Scientific Reports"
DOI: 10.1038/s41598-020-63191-5
Abstract: E-mail has become the main carrier of spreading malicious software and been widely used for phishing, even high-level persistent threats. The e-mail accounts with high social reputation are primary targets to be attacked and utilized… read more here.
Keywords: mail account; based graph; graph mining; account probing ... See more keywords
Structural reinforcement-based graph convolutional networks
Sign Up to like & getrecommendations! Published in 2022 at "Connection Science"
DOI: 10.1080/09540091.2022.2151977
Abstract: Graph Convolutional Network (GCN) is a tool for feature extraction, learning, and inference on graph data, widely applied in numerous scenarios. Despite the great success of GCN, it performs weakly under some application conditions, such… read more here.
Keywords: graph convolutional; reinforcement based; convolutional networks; structural reinforcement ... See more keywords
Decoupling Identification Method of Continuous Working Conditions of Diesel Engines Based on a Graph Self-Attention Network
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3164077
Abstract: Complex and changeable working conditions are important factors affecting the accuracy and robustness of diesel engine fault diagnosis models. Working condition identification can provide a basic reference for the unit operation state, which is of… read more here.
Keywords: continuous working; condition; working condition; identification ... See more keywords
Biomedical Word Sense Disambiguation Based on Graph Attention Networks
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3224802
Abstract: Biomedical words have many semantics. Biomedical word sense disambiguation (WSD) is an important research issue in biomedicine field. Biomedical WSD refers to the process of determining meanings of ambiguous word according to its context. It… read more here.
Keywords: sense disambiguation; disambiguation; word; biomedical word ... See more keywords
Scientific Documents Retrieval Based on Graph Convolutional Network and Hesitant Fuzzy Set
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3259234
Abstract: Previous scientific literature retrieval methods, which are based on mathematical expression, ignore the literature attributes and the association between the literature, and the retrieval accuracy was affected. In this study, literature retrieval model based on… read more here.
Keywords: graph convolutional; retrieval; literature retrieval; literature ... See more keywords
Semisupervised Hyperspectral Image Classification via Superpixel-Based Graph Regularization With Local and Nonlocal Features
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.2022.3191692
Abstract: Although a graph-based semisupervised learning (SSL) approach can utilize limited numbers of labeled samples for hyperspectral image (HSI) classification, it is difficult to use the large amount of pixels in an HSI to construct a… read more here.
Keywords: superpixel based; classification; graph regularization; based graph ... See more keywords