Results 151 to 160 of about 7,364 (234)

GraphNeuralCloth: A Graph‐Neural‐Network‐Based Framework for Non‐Skinning Cloth Simulation

Advanced Intelligent Systems, EarlyView.
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, Xiaomei Wang, Xiaoqi Song, Chenchen Fan, Bohao Zhu, Jianan Peng, Qixin Liang, James Lam, Kam‐Yim Sze, Ka‐Wai Kwok   +9 more
wiley   +1 more source

Multi-stage iterative compressed sensing framework based on DIFF transformer and ISTA for remote sensing images. [PDF]

Sci Rep
Wang R, Fang Y.
europepmc   +1 more source

A Flexible and Energy‐Efficient Compute‐in‐Memory Accelerator for Kolmogorov–Arnold Networks

Advanced Intelligent Systems, EarlyView.
This article presents KA‐CIM, a compute‐in‐memory accelerator for Kolmogorov–Arnold Networks (KANs). It enables flexible and efficient computation of arbitrary nonlinear functions through cross‐layer co‐optimization from algorithm to device. KA‐CIM surpasses CPU, ASIC, VMM‐CIM, and prior KAN accelerators by 1–3 orders of magnitude in energy‐delay ...
Chirag Sudarshan, Oliver Artner, Paul‐Philipp Manea, Sebastian Siegel, Susanne Hoffmann‐Eifert, Regina Dittmann, John Paul Strachan   +6 more
wiley   +1 more source

A hallucination detection and mitigation framework for faithful text summarization using LLMs. [PDF]

Sci Rep
Liu S, Gao Y, Li S, Wang P, Wang T.
europepmc   +1 more source

Iterative decoding of product codes

, 2003
Iterative decoding of block codes is a rather old subjectthat regained much interest recently. The main idea behinditerative decoding is to break up the decoding problem into asequence of stages, iterations, such that each stage utilizesthe output from the previous stages to formulate its ownresult.
openaire   +1 more source

Deformable Attention Multiscale Feature Fusion Network‐Dehaze: An Adaptive Image Dehazing Method Based on Deformable Attention Multiscale Fusion Network

Advanced Intelligent Systems, EarlyView.
This paper presents the deformable attention multiscale feature fusion network‐dehaze adaptive image dehazing network, which integrates three core modules (revised residual shrinkage unit, multiscale attention, cross‐scale feature fusion). It incorporates deformable convolution and multiscale attention mechanisms to address the detail loss issue of ...
Ruipeng Wang, Yajun Chen, Hao Liu, Mingrui Li, Zhiqi Li   +4 more
wiley   +1 more source

Neuromorphic computing paradigms enhance robustness through spiking neural networks. [PDF]

Nat Commun
Ding J, Yu Z, Liu JK, Huang T.
europepmc   +1 more source

Weighted Sum-Rate Maximization and Task Completion Time Minimization for Multi-Tag MIMO Symbiotic Radio Networks. [PDF]

Sensors (Basel)
Suo L, Wang D, Zhou W, Peng X.
europepmc   +1 more source

A Novel Deep Temporal Feature Enhanced Just‐in‐Time Learning Framework for Predicting Rare Earth Component Content

Asia-Pacific Journal of Chemical Engineering, EarlyView.
ABSTRACT Real‐time online detection of rare earth element component contents is a crucial link in ensuring the stable production of the rare earth extraction and separation industry and improving the quality of rare earth products. The traditional methods for predicting the content of rare earth element components based on just‐in‐time learning fail to
Zhaohui Huang, Liangfang Liao, Chunfa Liao, Hui Zhang, Tao Qi, Rongxiu Lu, Wenhao Dai   +6 more
wiley   +1 more source

Individualized brain-computer interface for people with disabilities: a review. [PDF]

Front Hum Neurosci
Saha S, Karlsson P, Anderson C, Kavehei O, McEwan A.   +4 more
europepmc   +1 more source