Comparing Classification Methods for Longitudinal fMRI Studies
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Publication:3057223
DOI10.1162/NECO_a_00024zbMath1208.68193DBLPjournals/neco/SchmahYZHSS10WikidataQ51665654 ScholiaQ51665654MaRDI QIDQ3057223
Grigori Yourganov, Steven L. Small, Stephen C. Strother, Tanya Schmah, Richard S. Zemel, Geoffrey E. Hinton
Publication date: 24 November 2010
Published in: Neural Computation (Search for Journal in Brave)
Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)
Related Items (3)
Efficient classification for longitudinal data ⋮ Multivoxel pattern analysis for fMRI data: a review ⋮ Olfactory Recognition Based on EEG Gamma-Band Activity
Cites Work
- Learning to decode cognitive states from brain images
- Reducing the Dimensionality of Data with Neural Networks
- Training Products of Experts by Minimizing Contrastive Divergence
- Brain Reading Using Full Brain Support Vector Machines for Object Recognition: There Is No “Face” Identification Area
- A Fast Learning Algorithm for Deep Belief Nets
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