HIGHLIGHTS
- who: Posted Date February and collaborators from the (UNIVERSITY) have published the article: Automatic classi�cation of brain magnetic resonance images with hypercolumn deep features and machine learning, in the Journal: (JOURNAL)
- what: In this study, machine_learning experiments were carried out by utilizing hold-out and 5-fold crossvalidation techniques on the balanced dataset. After the model was built, the keypoint detection on the test dataset and the extraction of hypercolumn deep features from the keypoints were carried out. Different from the study of Toğaçar et_al , this study proposes a novel approach including . . .
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