• Complex
  • Title
  • Keyword
  • Abstract
  • Scholars
  • Journal
  • ISSN
  • Conference
成果搜索

author:

Wang, F. (Wang, F..) [1] | Ke, H. (Ke, H..) [2] | Ma, H. (Ma, H..) [3] | Tang, Y. (Tang, Y..) [4]

Indexed by:

Scopus

Abstract:

Temporal-frequency characteristics in fMRI data are key to distinguishing Autism Spectrum Disorder (ASD) from neurotypical individuals. However, the non-linearity and multidimensionality of fMRI data pose significant challenges. To address these, we introduce a Deep Non-linear Factorization method with a Wavelet Temporal-Frequency Attention module (Deep WTFAF) tailored for multidimensional fMRI analysis. By leveraging the wavelet domain, our approach applies temporal-frequency attention to assign weights to significant features, enhancing critical data while reconstructing incomplete fMRI data. This method enables deep non-linear factorization and effective feature representation for subsequent classification tasks. Validated on ASD-related fMRI datasets, Deep WTFAF outperforms traditional methods, maintaining essential information and ensuring robustness against high-dimensional and incomplete data. Stability theory proof further confirms the model's reliability, crucial for clinical applications like neurological disorder classification. © 2025 Elsevier Ltd

Keyword:

ASD Classification Deep learning Factorization Wavelet attention

Community:

  • [ 1 ] [Wang F.]School of physics and electronic science, Hubei Normal University, Hubei, Huangshi, 435002, China
  • [ 2 ] [Ke H.]Computer School (Huangshi Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence), Hubei Polytechnic University, Hubei, Huangshi, 435003, China
  • [ 3 ] [Ke H.]School of Computer Science, Wuhan University, Hubei, Wuhan, 430072, China
  • [ 4 ] [Ma H.]Medical School, Hubei Polytechnic University, Hubei, Huangshi, 435003, China
  • [ 5 ] [Tang Y.]College of Computer and Data Science, Fuzhou University, Fujian, Fuzhou, 350108, China

Reprint 's Address:

Email:

Show more details

Related Keywords:

Source :

Pattern Recognition

ISSN: 0031-3203

Year: 2025

Volume: 165

7 . 5 0 0

JCR@2023

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

Affiliated Colleges:

Online/Total:208/10755918
Address:FZU Library(No.2 Xuyuan Road, Fuzhou, Fujian, PRC Post Code:350116) Contact Us:0591-22865326
Copyright:FZU Library Technical Support:Beijing Aegean Software Co., Ltd. 闽ICP备05005463号-1