IEEE

HFGNN: Efficient Graph Neural Networks Using Hub-Fringe Structures

Abstract: Existing message passing-based and transformer-based graph neural networks (GNNs) cannot satisfy requirements for learning representative graph embeddings due to restricted receptive fields, ...
IEEE

An Improved Image Up-Scaling Technique using Optimize Filter and Iterative Gradient Method

Abstract: In numerous realtime applications, image upscaling often relies on several polynomial techniques to reduce computational complexity. However, in high-resolution (HR) images, such polynomial ...
IEEE

Heat Stress Forecasting and Mitigation in Outdoor Worker Safety Using Gradient Boosting and IoT Technologies

Abstract: Workers are more vulnerable to heat stress when working outdoors. Thus, accurate predictions and measures to reduce its effects are crucial. This paper presents a new method that combines ...
IEEE

Trajectory-Oriented Control Using Gradient Descent: An Unconventional Approach

Abstract: In this work, we introduce a novel gradient descent-based approach for optimizing control systems, leveraging a new representation of stable closed-loop dynamics as a function of two ...
IEEE

Uncertainty Quantification for Traffic Forecasting Using Deep-Ensemble-Based Spatiotemporal Graph Neural Networks

Abstract: Deep-learning-based data-driven forecasting methods have achieved impressive results for traffic forecasting. Specifically, spatiotemporal graph neural networks have emerged as a promising ...
IEEE

Hyperspectral Unmixing Using Higher-Order Graph Regularized NMF With Adaptive Feature Selection

Abstract: Recently, graph learning methods have attracted much research attention, which uses first-order nearest-neighbor relation between pixels to construct adjacency graphs for capturing smooth ...
IEEE

Manifold Graph Signal Restoration Using Gradient Graph Laplacian Regularizer

Abstract: In the graph signal processing (GSP) literature, graph Laplacian regularizer (GLR) was used for signal restoration to promote piecewise smooth / constant reconstruction with respect to an ...
IEEE

Extended Target Reconstruction for Real Aperture Radar Using Sparse and 2-D High-Order Gradient Hybrid Prior Bayesian Method

Abstract: The reconstruction of the scale and shape information of extended targets is a major challenge for real aperture radar (RAR). Due to the limitation of angular resolution, the reconstruction ...
IEEE

High-Resolution Quasi-Geoid Recovery Over Coastal Zone by Using Airborne Gravity Gradient Data

Abstract: The potential of using airborne gravity gradient tensor (GGT) for coastal quasi-geoid (QG) refinement is explored, and the contributions introduced from individual GGT components and their ...
IEEE

Dholes Hunting—A Multi-Local Search Algorithm Using Gradient Approximation and Its Application for Blockchain Consensus Problem

Abstract: This study introduces a brand-new swarm-inspired algorithm dubbed dholes hunting-based optimization (DhoH) based on an animal hunting strategy to solve global optimization problems. The ...
IEEE

Benchmarking Feature Extractors for Prostate Cancer Detection Using Graph Attention Networks: A Focus on Foundation Models

Abstract: Accurate prostate cancer detection from Whole-Slide Images (WSIs) is critical for improving diagnostics. This study benchmarks 10 foundation models as feature extractors for graph-based ...
kyivindependent

Ukraine could soon deploy 1,000 interceptor drones per day, defense minister says

Defense Minister Denys Shmyhal delivers a speech during a joint press conference with Polish Deputy Prime Minister and Defense Wladyslaw Kosiniak-Kamysz in Kyiv ...