Results 171 to 180 of about 249,760 (328)

Meander‐Bend Erosion Dynamics Along a Gravel‐Bed River: Insights From Short‐Term UAV Monitoring

River Research and Applications, EarlyView.
ABSTRACT Riverbank erosion is a natural process in meandering rivers that contributes to sediment supply and geomorphic diversity, yet it can threaten infrastructure and human activities within the floodplain. Recently, many studies have used high‐resolution remote sensing technologies to measure bank erosion, but they often focus on technical aspects ...
Katarina Pavlek, Mateo Gašparović, Tomáš Galia   +2 more
wiley   +1 more source

Existence and stabilization results for a singular parabolic equation involving the fractional Laplacian [PDF]

, 2017
Jacques Giacomoni, Tuhina Mukherjee, K. Sreenadh   +2 more
openalex   +1 more source

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

Nonlocal $p$-Laplacian evolution problems on graphs [PDF]

, 2016
Yosra Hafiene, Jalal Fadili, Abderrahim Elmoataz   +2 more
openalex   +1 more source

Laplacian Dynamics on Cographs: Controllability Analysis Through Joins and Unions [PDF]

, 2020
Shima Sadat Mousavi, Mohammad Haeri, Mehran Mesbahi   +2 more
openalex   +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

A multiscale theory for network advection- reaction-diffusion. [PDF]

J Math Biol
Oliveri H, Cozzolino E, Goriely A.
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

Flows of Conformally Coclosed G 2 -Structures with Dilaton. [PDF]

J Geom Anal
Karigiannis S, Picard S, Suan C.
europepmc   +1 more source

Short‐Term Multi‐Horizon Line Loss Rate Forecasting of a Distribution Network Using Attention‐GCN‐LSTM

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Accurately predicting line loss rates is crucial for effective management in distribution networks, particularly for short‐term multihorizon forecasts ranging from 1 hour to 1 week. In this study, we propose attention‐GCN–LSTM, a novel method that integrates graph convolutional networks (GCN), long short‐term memory (LSTM) and a three‐level ...
Jie Liu, Yijia Cao, Yong Li, Yixiu Guo, Wei Deng   +4 more
wiley   +1 more source