Periodic and subharmonic solutions for a 2nth-order p-Laplacian difference equation containing both advances and retardations [PDF]
, 2018 Peng Mei, Zhan Zhou
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CAAI Transactions on Intelligence Technology, EarlyView.Abstract Graph neural networks (GNNs) have revolutionised the processing of information by facilitating the transmission of messages between graph nodes. Graph neural networks operate on graph‐structured data, which makes them suitable for a wide variety of computer vision problems, such as link prediction, node classification, and graph classification.
Amit Sharma +4 more
wiley +1 more source
Multiplicity and asymptotic behavior of solutions to a class of Kirchhoff-type equations involving the fractional p-Laplacian. [PDF]
J Inequal Appl, 2018 Shen L.
europepmc +1 more source
Existence Theorems for Some Classes of Boundary Value Problems Involving the P(X)-Laplacian
, 2008 Ionicǎ Andrei
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On the periodic boundary value problem for Duffing type fractional differential equation with p-Laplacian operator [PDF]
, 2015 Hua Jin, Wenbin Liu
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Enhancing generalized spectral clustering with embedding Laplacian graph regularization
CAAI Transactions on Intelligence Technology, EarlyView.Abstract An enhanced generalised spectral clustering framework that addresses the limitations of existing methods by incorporating the Laplacian graph and group effect into a regularisation term is presented. By doing so, the framework significantly enhances discrimination power and proves highly effective in handling noisy data.
Hengmin Zhang +5 more
wiley +1 more source
Quantitative Assessment of Focus Quality in Whole-Slide Imaging of Thyroid Liquid-Based Cytology Using Laplacian Variance. [PDF]
Endocr PatholJung CK, Kim C, Jeon S, Bychkov A.
europepmc +1 more source
Pullback attractors for nonautonomous parabolic equations involving weighted p-Laplacian operators [PDF]
, 2011 Cung The Anh, Bao Quoc Tang
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Boosted unsupervised feature selection for tumor gene expression profiles
CAAI Transactions on Intelligence Technology, EarlyView.Abstract In an unsupervised scenario, it is challenging but essential to eliminate noise and redundant features for tumour gene expression profiles. However, the current unsupervised feature selection methods treat all samples equally, which tend to learn discriminative features from simple samples.
Yifan Shi +5 more
wiley +1 more source
CAAI Transactions on Intelligence Technology, EarlyView.Abstract In intelligent transportation systems, object detection for a surveillance video is one of the important functions. The performance of existing surveillance video object detection algorithms is affected by the conflict between the features of the objects, which leads to a decline in precision.
Yang He +5 more
wiley +1 more source