LAUSR

About LAUSR
Donate
Contact Us

Follow us:

You are not signed in:

Sign Up!


   Articles with "dual graph" as a keyword



Dual graph-based vulnerability evaluation for power grids considering fault correlation by utilizing improved e-index method

Sign Up to like & get
recommendations! Published in 2025 at "Physica Scripta"

DOI: 10.1088/1402-4896/ae0f5c

Abstract: To identify the vulnerable lines accurately and reduce the risk of major outages, a vulnerability evaluation method is proposed based on an improved e-index applied to a dual-graph of power systems. Firstly, the weighted dual… read more here.

Keywords: vulnerability evaluation; dual graph; index; improved index ... See more keywords

scHiCPTR: unsupervised pseudotime inference through dual graph refinement for single-cell Hi-C data

Sign Up to like & get
recommendations! Published in 2022 at "Bioinformatics"

DOI: 10.1093/bioinformatics/btac670

Abstract: MOTIVATION The emerging single-cell Hi-C technology provides opportunities to study dynamics of chromosomal organization. How to construct a pseudotime path using single-cell Hi-C contact matrices to order cells along developmental trajectory is a challenging topic,… read more here.

Keywords: cell; pseudotime; schicptr unsupervised; graph refinement ... See more keywords

Dual Graph Neural Networks for Dynamic Users’ Behavior Prediction on Social Networking Services

Sign Up to like & get
recommendations! Published in 2024 at "IEEE Transactions on Computational Social Systems"

DOI: 10.1109/tcss.2024.3409383

Abstract: Social network services (SNSs) provide platforms where users engage in social link behavior (e.g., predicting social relationships) and consumption behavior. Recent advancements in deep learning for recommendation and link prediction explore the symbiotic relationships between… read more here.

Keywords: graph neural; dual graph; prediction; network ... See more keywords

Joint Adaptive Dual Graph and Feature Selection for Domain Adaptation

Sign Up to like & get
recommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems for Video Technology"

DOI: 10.1109/tcsvt.2021.3073937

Abstract: Domain adaptation aims to exploit domain-invariant features by aligning the cross-domain distributions in the manifold subspace for applying the classifier trained on the source domain to the target domain. However, two limitations may still deteriorate… read more here.

Keywords: domain; dual graph; domain adaptation; feature selection ... See more keywords

Dual Graph Inference Network for Weakly Supervised Semantic Segmentation

Sign Up to like & get
recommendations! Published in 2025 at "IEEE Transactions on Circuits and Systems for Video Technology"

DOI: 10.1109/tcsvt.2025.3544331

Abstract: Establishing global contextual relationships between objects is crucial for weakly supervised semantic segmentation (WSSS) tasks that lack pixel-level labels. Limited by the efficiency of convolutional operations in capturing long-range dependencies with a limited receptive field… read more here.

Keywords: graph reasoning; weakly supervised; dual graph; semantic segmentation ... See more keywords

Incomplete Multilabel Feature Selection via Dynamic Dual-Graph Optimization and Fuzzy Feature Interaction

Sign Up to like & get
recommendations! Published in 2025 at "IEEE Transactions on Fuzzy Systems"

DOI: 10.1109/tfuzz.2025.3595942

Abstract: Multilabel feature selection (MFS) plays a vital role in enhancing model performance by identifying the most relevant features. However, most existing methods assume complete feature information and overlook the potential issue of missing features in… read more here.

Keywords: graph optimization; dual graph; feature; interaction ... See more keywords

Robust Dual Graph Self-Representation for Unsupervised Hyperspectral Band Selection

Sign Up to like & get
recommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"

DOI: 10.1109/tgrs.2022.3203207

Abstract: Unsupervised band selection aims to select informative spectral bands to preprocess hyperspectral images (HSIs) without using labels. Traditional band selection methods only work well on Euclidean data, but ignore structural information of pixels and spectral… read more here.

Keywords: band; dual graph; band selection; robust dual ... See more keywords

Few-Shot Learning for Fault Diagnosis With a Dual Graph Neural Network

Sign Up to like & get
recommendations! Published in 2023 at "IEEE Transactions on Industrial Informatics"

DOI: 10.1109/tii.2022.3205373

Abstract: Mechanical fault diagnosis is crucial to ensure the safe operations of equipment in intelligent manufacturing systems. Deep learning-based methods have been recently developed for fault diagnosis due to their advantages in feature representation. However, most… read more here.

Keywords: fault diagnosis; diagnosis; graph neural; shot learning ... See more keywords

Dual-Graph Collaboration: Bidirectional Fusion Graph Convolution Network for Structure Multidefect Positioning and Assessment

Sign Up to like & get
recommendations! Published in 2024 at "IEEE Transactions on Industrial Informatics"

DOI: 10.1109/tii.2024.3435441

Abstract: Graph convolution network can extract structural multidefect information well, and has been widely concerned in the field of structural damage detection. However, it is difficult to locate and evaluate defects of different sizes only using… read more here.

Keywords: structure; convolution network; dual graph; graph convolution ... See more keywords

Multimodal Dual-Graph Collaborative Network With Serial Attentive Aggregation Mechanism for Micro-Video Multi-Label Classification

Sign Up to like & get
recommendations! Published in 2025 at "IEEE Transactions on Multimedia"

DOI: 10.1109/tmm.2025.3542895

Abstract: The increasing commercial value of micro-videos has spurred a rising demand for grasping their contents. The abundant multimodal cues in micro-videos exhibit substantial potential in enhancing content comprehension. However, effectively harnessing the collaborative characteristics across… read more here.

Keywords: multi label; dual graph; serial attentive; network ... See more keywords

Dual-Graph Global and Local Concept Factorization for Data Clustering.

Sign Up to like & get
recommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"

DOI: 10.1109/tnnls.2022.3177433

Abstract: Considering a wide range of applications of nonnegative matrix factorization (NMF), many NMF and their variants have been developed. Since previous NMF methods cannot fully describe complex inner global and local manifold structures of the… read more here.

Keywords: concept factorization; local concept; graph global; factorization ... See more keywords