Graph convolutional neural network

Results 241 to 250 of about 5,698,498 (295)

A Soft Robotic Finger With Deep Learning‐Enhanced Tactile Sensing for Texture and Softness Recognition

Advanced Intelligent Systems, EarlyView.
Inspired by human touch, a tendon‐driven soft robotic finger combines multimodal tactile sensing and deep learning to simultaneously perceive texture and softness on deformable surfaces. A CNN‐LSTM model fuses pressure, accelerometer, and gyroscope signals to accurately classify material properties, achieving up to 95.4% texture and 97.0% softness ...
Gorkem Anil Al +3 more
wiley +1 more source

Essential genes identification model based on sequence feature map and graph convolutional neural network. [PDF]

BMC Genomics
Hu W, Li M, Xiao H, Guan L.
europepmc +1 more source

Behaviorally Adaptive and Inclusive Advanced Driver‐Assistance Systems

Advanced Intelligent Systems, EarlyView.
Advanced driver‐assistance systems (ADASs) are mapped as evolving human‐centered, adaptive technologies linking sensing, driver monitoring, AR/HUD interfaces, patents, regulation, and inclusive design. The review identifies gaps in real‐world evidence, diverse‐driver validation, gaze metrics, and governance, outlining a roadmap for safer, behaviorally ...
Jana Skirnewskaja +2 more
wiley +1 more source

Exploiting Edge Semantics in Job Shop Scheduling Problem With Heterogeneous Graph Transformers

Advanced Intelligent Systems, EarlyView.
A heterogeneous graph transformer (HGT) is introduced for reinforcement learning‐based job shop scheduling by explicitly distinguishing precedence and machine‐contention relations through edge‐type‐specific attention. The proposed framework learns richer scheduling representations, improves decision quality over homogeneous graph models, and highlights
Bulent Soykan, Fatih Kasimoglu
wiley +1 more source

Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy

Advanced Intelligent Systems, EarlyView.
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne +5 more
wiley +1 more source

Graph Neural Network‐Based Reinforcement Learning for Decentralized Multi‐Robot Manipulation

Advanced Intelligent Systems, EarlyView.
Robot arms lifting a large object face a trade‐off: centralized controllers explode in parameters, while decentralized ones cannot coordinate. A GNN resolves this—each arm runs its own network but acts on the full team state, achieving centralized‐level coordination with decentralized execution. Trained across team sizes, a single policy scales to four‐
Tong Chen, Bo Fu, Dawn Tilbury, Kira Barton +3 more
wiley +1 more source

autoscoRA: Deep Learning to Automate Sharp/van der Heijde Scoring of Radiographic Damage in Rheumatoid Arthritis

Arthritis &Rheumatology, EarlyView.
Objective Regular imaging by conventional radiography to assess for joint damage is a cornerstone in the management of rheumatoid arthritis. Scoring systems to quantify such damage, such as the widely used Sharp/van der Heijde (SvdH) score, are limited by the requirement of time and experienced staff as well as intra‐ and interrater variability.
Thomas Deimel +6 more
wiley +1 more source

Visualizing ESG Signaling Through User‐Generated Content: A Strategic Foresight Framework for Symbolic Legitimacy in Hospitality Branding

Business Strategy and the Environment, EarlyView.
ABSTRACT Social media platforms today have become essential for consumer‐brand interactions, with visual content playing a pivotal role in shaping engagement and brand perception. Although text‐based user‐generated content (UGC) has been widely studied, the potential of visual UGC, particularly in the travel, tourism and hospitality (TTH) sector ...
Chinchu Abraham, Pabitra Mitra, Sujoy Bhattacharya +2 more
wiley +1 more source

Brain age predicted using graph convolutional neural network explains neurodevelopmental trajectory in preterm neonates. [PDF]

Eur Radiol
Liu M +14 more
europepmc +1 more source

Mitigating the Heat: The Role of AI Technology in Shielding Corporate Environmental Performance From Extreme Temperatures—Difference‐in‐Differences Evidence From Chinese Listed Firms

Business Strategy and the Environment, EarlyView.
ABSTRACT Extreme heat has become a recurring operational challenge that disrupts production, raises energy and maintenance needs, and makes it harder for firms to sustain environmental performance. However, it remains less clear whether AI‐related capability is associated with firms' ability to maintain environmental performance under recurring extreme‐
Shangze Dai, Xinde James Ji, Kai Huang
wiley +1 more source

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graph convolutional neural networks

graph convolutional network
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