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 insight </ p ecosystem also provides brain tractometry processing brain connections also demonstrate software ecosystem integrative ecosystem transformative environment taken together subject age predictive analysis org </ group differences extract insights extensible tools different datasets characteristic structure based data analysis tasks >— provide
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The effects of data augmentation on NN age prediction performance.

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