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Psychiatric Disorders Classification with 3D Convolutional Neural Networks.

, , , , и . INNSBDDL, стр. 48-57. Springer, (2019)

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When the single matters more than the group: Very high false positive rates in single case Voxel Based Morphometry., , , и . NeuroImage, (2013)Category Deficits and Paradoxical Dissociations in Alzheimer's Disease and Herpes Simplex Encephalitis., и . J. Cogn. Neurosci., 17 (9): 1453-1459 (2005)Using Blink Rate to Detect Deception: A Study to Validate an Automatic Blink Detector and a New Dataset of Videos from Liars and Truth-Tellers., , , , , , , и . HCI (3), том 12183 из Lecture Notes in Computer Science, стр. 494-509. Springer, (2020)Automatic Detection of Cross-language Verbal Deception., , , , и . CogSci, cognitivesciencesociety.org, (2020)Detecting deception through facial expressions in a dataset of videotaped interviews: A comparison between human judges and machine learning models., , , , и . Comput. Hum. Behav., (2022)Forged handwriting verification: a public domain dataset for training machine learning models., , , , , и . IJCNN, стр. 1-8. IEEE, (2022)Detecting Identity Deception in Online Context: A Practical Approach Based on Keystroke Dynamics., , , и . AHFE (19), том 1219 из Advances in Intelligent Systems and Computing, стр. 41-48. Springer, (2020)DecOp: A Multilingual and Multi-domain Corpus For Detecting Deception In Typed Text., , , , и . LREC, стр. 1423-1430. European Language Resources Association, (2020)Type Me the Truth!: Detecting Deceitful Users via Keystroke Dynamics., , , , , и . ARES, стр. 60:1-60:6. ACM, (2017)The Detection and the Neural Correlates of Behavioral (Prior) Intentions., , , , и . J. Cognitive Neuroscience, 23 (12): 3888-3902 (2011)