The effects of data augmentation on NN age prediction performance.

The effects of data augmentation on NN age prediction performance.

<p>Data augmentation introduces random noise to each sample of the training data in each batch of training. This method can help NN algorithms with a large number of parameters generalize better, by preventing the memorization of the samples in the training set. When augmentation levels grow v...

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Main Author: John Kruper (18809386) (author)
Other Authors: Adam Richie-Halford (7874510) (author), Joanna Qiao (22057760) (author), Asa Gilmore (18809395) (author), Kelly Chang (22057763) (author), Mareike Grotheer (22057766) (author), Ethan Roy (22057769) (author), Sendy Caffarra (3720577) (author), Teresa Gomez (14486220) (author), Sam Chou (22057772) (author), Matthew Cieslak (3112521) (author), Serge Koudoro (11837609) (author), Eleftherios Garyfallidis (3158781) (author), Theodore D. Satterthwaite (11006319) (author), Jason D. Yeatman (7304606) (author), Ariel Rokem (1369482) (author)
Published: 2025
Subjects:
Biochemistry
Biological Sciences not elsewhere classified
Information Systems not elsewhere classified
tissue properties within
including hypothesis testing
computational advances implemented
assess physical properties
tractometry uses diffusion
div >< p
statistical analysis methods
software offer orders
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ecosystem also provides
brain tractometry processing
brain connections
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software ecosystem
integrative ecosystem
transformative environment
taken together
subject age
predictive analysis
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group differences
extract insights
extensible tools
different datasets
characteristic structure
based data
analysis tasks
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