Results 51 to 60 of about 179,952 (279)

DeepMapper: Attention‐Based AutoEncoder for System Identification in Wound Healing and Stage Prediction

Advanced Intelligent Discovery, EarlyView.
The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu, Ksenia Zlobina, Michael Briden, Oscar Avalos, Héctor Carrión, Sebastian Osorio, Hsin‐ya Yang, Alexandra Nava, Michelle D. Bagood, Marco Rolandi, Roslyn Rivkah Isseroff, Marcella Gomez   +11 more
wiley   +1 more source

Analytic Solutions to Reflection-Transmission Problem of Interface in Anisotropic Ice Sheet

International Journal of Antennas and Propagation, 2020
The rheology and evolution of the polar ice sheet are deeply influenced by the anisotropy of ice crystals. Studying the anisotropy of ice crystals can help to well understand and predict the behavior of the polar ice sheet and then the sea level rising ...
Bangbing Wang, Honkuan Wong
doaj   +1 more source

Adaptive Macroscopic Ensemble Allocation for Robot Teams Monitoring Spatiotemporal Processes

Advanced Intelligent Systems, EarlyView.
We propose an online, environment feedback‐driven macroscopic ensemble approach to adapt robot team task allocation in spatiotemporal environments by controlling robot populations rather than assigning individual robots, all while maintaining robust team performance even for small teams. Our simulation and experimental results show better or comparable
Victoria Edwards, Thales C. Silva, M. Ani Hsieh   +2 more
wiley   +1 more source

The Spectrum and Eigenvectors of the Laplacian Matrices of the Brualdi-Li Tournament Digraphs

Journal of Applied Mathematics, 2014
Let m≥1 be an integer, let ℬ2m denote the Brualdi-Li matrix of order 2m, and let ℒℬ2m denote the Laplacian matrices of Brualdi-Li tournament digraphs. We obtain the eigenvalues and eigenvectors of ℒℬ2m.
Xiaogen Chen
doaj   +1 more source

Classifications of surface waves in magneto-electro-elastic materials

Results in Physics, 2023
The present study investigates the classifications of surface waves in magneto-electro-elastic materials. First, the standard eigenrelation, relating to the generalized displacement and the generalized tractions, is derived from the governing equations ...
Li Li, Man Lan, Peijun Wei, Qian Zhang
doaj   +1 more source

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source

Spectral pruning of fully connected layers

Scientific Reports, 2022
Training of neural networks can be reformulated in spectral space, by allowing eigenvalues and eigenvectors of the network to act as target of the optimization instead of the individual weights.
Lorenzo Buffoni, Enrico Civitelli, Lorenzo Giambagli, Lorenzo Chicchi, Duccio Fanelli   +4 more
doaj   +1 more source

Eigenvectors of block circulant and alternating circulant matrices [PDF]

, 2005
The eigenvectors and eigenvalues of block circulant matrices had been found for real symmetric matrices with symmetric submatrices, and for block circulant matrices with circulant submatrices. The eigenvectors are now found for general block circulant
Tee, Garry J.
core   +1 more source

An Integrated and Robust Deep Learning Framework for Denoising and Analyzing Single‐Cell Spatial Transcriptomics

Advanced Intelligent Systems, EarlyView.
Single‐cell Spatial Transcriptomics Analysis and Denoising Engine is introduced as a unified deep learning framework that jointly performs denoising, clustering, and gene prioritization in spatial transcriptomics. By integrating linear and nonlinear representations within a dual‐channel architecture, it improves robustness and accuracy, uncovers ...
Yaxuan Cui, Yang Cui, Ruheng Wang, Xin Zeng, Zheyong Zhu, Ding Yi, Ruihua Guo, Tetsuya Sakurai, Kenta Nakai, Xiucai Ye, Leyi Wei, Yong Chen   +11 more
wiley   +1 more source

Evaluation of quantitative muscle MRI and an intelligent phenotyping housing system as advanced phenotyping methods in a mouse model of calpain 3‐deficient muscular dystrophy

Animal Models and Experimental Medicine, EarlyView.
We applied quantitative MRI of the lower limb and automated home‐cage phenotyping to a mouse model of calpainopathy to detect early disease changes. At 15 months, calpain 3‐deficient mice showed increased water T2 values correlating with immune cell infiltration in the soleus and gastrocnemius muscles, while assessment of motor activity revealed only ...
Nicolina Südkamp, Marlena Rohm, Gabriele Russo, Xavier Helluy, Abdulhadi Kocabas, Martijn Froeling, Felix Kleefeld, Denise Manahan‐Vaughan, Tobias Ruck, Frank Jacobsen, Matthias Vorgerd, Johannes Forsting, Lara Schlaffke   +12 more
wiley   +1 more source