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  2. List of datasets in computer vision and image processing

    en.wikipedia.org/wiki/List_of_datasets_in...

    CIFAR-100 Dataset Like CIFAR-10, above, but 100 classes of objects are given. Classes labelled, training set splits created. 60,000 Images Classification 2009 [18] [36] A. Krizhevsky et al. CINIC-10 Dataset A unified contribution of CIFAR-10 and Imagenet with 10 classes, and 3 splits. Larger than CIFAR-10.

  3. European Data Format - Wikipedia

    en.wikipedia.org/wiki/European_data_format

    European Data Format (EDF) is a standard file format designed for exchange and storage of medical time series.Being an open and non-proprietary format, EDF(+) is commonly used to archive, exchange and analyse data from commercial devices in a format that is independent of the acquisition system.

  4. 10–20 system (EEG) - Wikipedia

    en.wikipedia.org/wiki/10–20_system_(EEG)

    EEG electrode positions in the 10-10 system using modified combinatorial nomenclature, along with the fiducials and associated lobes of the brain. When recording a more detailed EEG with more electrodes, extra electrodes are added using the 10% division , which fills in intermediate sites halfway between those of the existing 10–20 system.

  5. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    Major advances in this field can result from advances in learning algorithms (such as deep learning), computer hardware, and, less-intuitively, the availability of high-quality training datasets. [1] High-quality labeled training datasets for supervised and semi-supervised machine learning algorithms are usually difficult and expensive to ...

  6. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

  7. General Data Format for Biomedical Signals - Wikipedia

    en.wikipedia.org/wiki/General_Data_Format_for...

    The original GDF specification was introduced in 2005 as a new data format to overcome some of the limitations of the European Data Format for Biosignals (EDF). GDF was also designed to unify a number of file formats which had been designed for very specific applications (for example, in ECG research and EEG analysis). [2]

  8. EEG analysis - Wikipedia

    en.wikipedia.org/wiki/EEG_analysis

    Brainstorm is a collaborative, open-source application dedicated to the analysis of brain recordings including MEG, EEG, fNIRS, ECoG, depth electrodes and animal invasive neurophysiology. [30] The objective of Brainstorm is to share a comprehensive set of user-friendly tools with the scientific community using MEG/EEG as an experimental technique.

  9. Quantitative electroencephalography - Wikipedia

    en.wikipedia.org/wiki/Quantitative...

    The analog signal comprises a microvoltage time series of the EEG, sampled digitally and sampling rates adequate to over-sample the signal (using the Nyquist principle of exceeding twice the highest frequency being detected). Modern EEG amplifiers use adequate sampling to resolve the EEG across the traditional medical band from DC to 70 or 100 ...