Results 71 to 80 of about 4,990,305 (257)
A Network Scanning Organization Discovery Method Based on Graph Convolutional Neural Network
InformationWith the quick development of network technology, the number of active IoT devices is growing rapidly. Numerous network scanning organizations have emerged to scan and detect network assets around the clock.
Pengfei Xue +4 more
doaj +1 more source
Low-Pass Graph Convolutional Network for Recommendation
, 2022 Spectral graph convolution is extremely time-consuming for large graphs, thus existing Graph Convolutional Networks (GCNs) reconstruct the kernel by a polynomial, which is (almost) fixed.
Qin, Zheng, Zhang, Zixin, Yu, Wenhui
core +1 more source
Broadening Hard‐Magnet Discovery Beyond Symmetry Constraints via Unified Effective Anisotropy
Advanced Science, EarlyView.A unified effective‐anisotropy descriptor (Keff) extends hard‐magnet screening across all seven crystal systems, beyond the uniaxial restriction of conventional searches. Machine‐learning screening of 9320 known ferromagnets and diffusion‐model generation together yield 38 rare‐earth‐free or ‐lean candidates with DFT‐validated magnetic hardness (κ > 1),
Hojae Kim +5 more
wiley +1 more source
SF-ICNN: Spectral–Fractal Iterative Convolutional Neural Network for Classification of Hyperspectral Images [PDF]
One primary concern in the field of remote-sensing image processing is the precise classification of hyperspectral images (HSIs). Lately, deep-learning models have demonstrated cutting-edge results in HSI classification.
Akbari, Vahid +5 more
core +1 more source
Advanced Science, EarlyView.A new data‐efficient framework combining DFT calculations, a neural network model, and automated graph analysis of catalytic reaction networks is proposed and applied to CO2 hydrogenation on transition metal nanoparticles. The analysis shows how efficient C2 oxygenate production requires a balance between CHx formation, C–C coupling, protonation, and ...
Mikhail V. Polynski, Sergey M. Kozlov
wiley +1 more source
A Novel DDoS Detection and Multi-Class Classification Method: A Graph Convolutional Network Approach [PDF]
Distributed Denial of Service (DDoS) is an attack that overwhelms the cyber critical infrastructure system with malicious packets causing it to become unresponsive, which precludes legitimate users from accessing the target system.
Saunders, Braden
core
Dual‐Module Near‐Infrared Fluorophores Discovery System via Knowledge Transfer
Advanced Science, EarlyView.This study presents a dual‐module deep learning system for the design of near‐infrared (NIR) fluorophores. A large molecular library is generated and analyzed, leading to the suggestions of promising candidates. The effectiveness of the system is further validated through the synthesis, characterization, and in vivo imaging, demonstrating its potential
Yixin Zhu +7 more
wiley +1 more source
Advanced Science, EarlyView.This study develops a multi‐dimensional vision Transformer‐based model, GAVR, to accurately distinguish gastric cancer T4a/b stages preoperatively. Validated across multi‐center cohorts, it achieves excellent performance and significantly improves radiologists’ diagnostic accuracy, offering a promising tool for clinical decision‐making.
Guoliang Zheng +20 more
wiley +1 more source
A Deep Graph Structured Clustering Network
IEEE Access, 2020 Graph clustering is a fundamental task in data analysis and has attracted considerable attention in recommendation systems, mapping knowledge domain, and biological science. Because graph convolution is very effective in combining the feature information
Xunkai Li +5 more
doaj +1 more source
This is a tutorial paper on graph neural networks including ChebNet, graph convolutional network, graph attention network, and graph autoencoder. It starts with Laplacian of graph, graph Fourier transform, and graph convolution. Then, it is explained how
Benyamin Ghojogh, Ali Ghodsi
core +1 more source