100 results for "classification" · page 3 of 10 · ranked by relevance
…In a 10-fold cross validation test, a classification accuracy over 80…
This dataset investigates brain signal-based emotion recognition through magnetoencephalography (MEG) recordings collected while participants viewed validated emotional video stimuli. It comprises three components: a large-scale online behavioral survey of 500 participants rating 40 video clips, head digitization data for co-registration, and MEG neural recordings from 23 participants viewing the same stimuli. Emotional states were assessed using Self-Assessment Manikin ratings, discrete emotion categories (PrEmo), and temporal highlight annotations, providing multi-faceted ground truth for affective neuroscience research.
…In this experiment, participants completed two tasks - classification and passive viewing. In…
FOODEEG is an open dataset of electroencephalographic (EEG) and behavioural responses to food images from 117 participants across two testing sessions. Session 1 involved a food categorisation task with continuous EEG recording, while Session 2 comprised a food go/no-go task and a food paired choice task, along with questionnaires on dietary style and eating motivations. The dataset also includes normative ratings on 22 food attributes collected from an independent online sample (N = 624), providing a rich resource for studying neural and behavioural correlates of food-related decision-making.
…In this experiment, participants completed two tasks - classification and passive viewing. In…
THINGS-EEG2 is a large-scale EEG dataset comprising recordings from 10 subjects viewing 16,540 distinct training images and 200 test images presented via rapid serial visual presentation at 5 Hz. The dataset includes 63-channel EEG data sampled at 1000 Hz across 4 sessions per subject, with approximately 32,540 training trials and 16,000 test trials, designed to support computational modeling of human visual object recognition. Stimuli are drawn from the THINGS database, and the dataset includes resting-state recordings and behavioral annotations for each trial.
…target and non-target event classifications. ## Dataset Summary | Property | Value | |---|---| | Subjects | 19…
This high-density EEG dataset comprises resting-state and task-based recordings from 23 healthy volunteers performing visual naming and spelling tasks. Collected between 2012-2013 at Rennes University Hospital using a 256-electrode EEG system, the dataset enables investigation of dynamic functional brain network reorganization during language production and cognitive processing. The study provides insights into spatiotemporal patterns of brain connectivity during object naming and orthographic tasks.
…computer interface applications, achieving mean classification accuracy of 66.2±4.8…
…computer interface applications, achieving mean classification accuracy of 73.3±8.9…