Results 251 to 260 of about 302,460 (378)

Image and video analysis using graph neural network for Internet of Medical Things and computer vision applications

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, Ashutosh Sharma, Alexey Tselykh, Alexander Bozhenyuk, Byung‐Gyu Kim   +4 more
wiley   +1 more source

Maximum principles for the fractional p-Laplacian and symmetry of solutions [PDF]

Advances in Mathematics, 2017
Wenxiong Chen, Congming Li
semanticscholar   +1 more source

Enhanced MRI-PET fusion using Laplacian pyramid and empirical mode decomposition for improved oncology imaging. [PDF]

PLoS One
Suryanarayana G, Nimmagadda SM, Nageswara Rao S, Y Mahnashi AM, Kondamuri SR, Hussain Ahmadini AA, Zaagan AA, Msmali AH.   +7 more
europepmc   +1 more source

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, Jian Yang, Bob Zhang, Yang Tang, Wenli Du, Bihan Wen   +5 more
wiley   +1 more source

Uniqueness for positive solutions of $p$-Laplacian problem in an annulus [PDF]

, 1999
Eric Nabana
openalex   +1 more source

Further Exploration of an Upper Bound for Kemeny's Constant. [PDF]

Entropy (Basel)
Kooij RE, Dubbeldam JLA.
europepmc   +1 more source

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, Kaixiang Yang, Mengzhi Wang, Zhiwen Yu, Huanqiang Zeng, Yang Hu   +5 more
wiley   +1 more source

Solving the $p$-Laplacian on manifolds [PDF]

, 1999
Marc Troyanov
openalex   +1 more source

Comparison theorems on H-type sub-Riemannian manifolds. [PDF]

Calc Var Partial Differ Equ
Baudoin F, Grong E, Rizzi L, Vega-Molino S.   +3 more
europepmc   +1 more source

Laplacian attention: A plug‐and‐play algorithm without increasing model complexity for vision tasks

CAAI Transactions on Intelligence Technology, Volume 10, Issue 2, Page 545-556, April 2025.
Abstract Most prevailing attention mechanism modules in contemporary research are convolution‐based modules, and while these modules contribute to enhancing the accuracy of deep learning networks in visual tasks, they concurrently augment the overall model complexity.
Xiaolei Chen, Yubing Lu, Runyu Wen
wiley   +1 more source