Results 191 to 200 of about 55,131 (288)
Performance of a GPU- and time-efficient pseudo-3D network for magnetic resonance image super-resolution and motion artifact reduction. [PDF]
Li H +10 more
europepmc +1 more source
A lightweight machine learning (ML)‐based thermal prediction framework is demonstrated and implemented on a field‐programmable gate array (FPGA). Using measured temperature data from a real chiplet, the approach enables real‐time, die‐level heat‐map inference with low power consumption, validating practical on‐chip thermal monitoring for advanced ...
Jun Ho Lee +4 more
wiley +1 more source
Review of large YOLOv8 and RT-DETR energy efficiency on edge devices for real-time detection. [PDF]
Suchý I, Turčaník M.
europepmc +1 more source
GraphNeuralCloth: A Graph‐Neural‐Network‐Based Framework for Non‐Skinning Cloth Simulation
This study presents a cloth motion capture system and a point‐cloud‐to‐mesh processing method to support the prediction of real‐world fabric deformation. GraphNeuralCloth, a graph neural‐network (GNN)‐based framework is also proposed to estimate the cloth morphology change in real time.
Yingqi Li +9 more
wiley +1 more source
Deep Reinforcement Learning Approaches for Sensor Data Collection by a Swarm of UAVs
This article presents four decentralized reinforcement learning algorithms for autonomous data harvesting and investigates how collaboration improves collection efficiency. It also presents strategies to minimize training times by improving model flexibility, enabling algorithms to operate with varying number of agents and sensors.
Thiago de Souza Lamenza +2 more
wiley +1 more source
ControlIt: A Universal Framework for Translational, Adaptive, and Online Brain–Computer Interfaces
Brain–computer interfaces (BCIs) lack a unified platform that works across signals and algorithms. ControlIt, an open‐source, modular ROS2‐based BCI framework supporting electroencephalography (EEG), electrocorticography (ECoG), and spike‐based decoding across both classification and regression tasks is presented.
Wanlin Yang +12 more
wiley +1 more source
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He +2 more
wiley +1 more source
Accelerating mesh-based Monte Carlo simulations using contemporary graphics ray-tracing hardware. [PDF]
Yan S, Dwyer D, Kaeli DR, Fang Q.
europepmc +1 more source
Enabling Stochastic Dynamic Games for Robotic Swarms
This paper scales stochastic dynamic games to large swarms of robots through selective agent modeling and variable partial belief space planning. We formulate these games using a belief space variant of iterative Linear Quadratic Gaussian (iLQG). We scale to teams of 50 agents through selective modeling based on the estimated influence of agents ...
Kamran Vakil, Alyssa Pierson
wiley +1 more source

