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Receptive Field Atlas and Related CNN Models., , , , , , , , , and 5 other author(s). Int. J. Bifurc. Chaos, 14 (2): 551-584 (2004)Automatic brain MRI motion artifact detection based on end-to-end deep learning is similarly effective as traditional machine learning trained on image quality metrics., , , , , , , , , and 1 other author(s). Medical Image Anal., (August 2023)FMRI repetition suppression for voices is modulated by stimulus expectations., , , , and . NeuroImage, (2013)Deformable models direct supervised guidance: A novel paradigm for automatic image segmentation., , , and . Neurocomputing, (2016)A Model for Classification Based on the Functional Connectivity Pattern Dynamics of the Brain., , , , and . ENIC, page 203-208. IEEE Computer Society, (2016)Multi-disciplinary Modality Classification for Medical Images, , , and . CLEF (Notebook Papers/Labs/Workshop), (2011)Modality Classification for Medical Images Using Sparse Coded Affine-Invariant Descriptors., , , and . PAKDD Workshops, volume 7769 of Lecture Notes in Computer Science, page 1-10. Springer, (2012)Research Paper: Semantic Classification of Diseases in Discharge Summaries Using a Context-aware Rule-based Classifier., , , and . JAMIA, 16 (4): 580-584 (2009)Neural mechanisms for voice recognition., , , , , and . NeuroImage, 52 (4): 1528-1540 (2010)Multi-disciplinary Modality Classification for Medical Images., , , and . CLEF (Notebook Papers/Labs/Workshop), volume 1177 of CEUR Workshop Proceedings, CEUR-WS.org, (2011)