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  2. NTU RGB-D dataset - Wikipedia

    en.wikipedia.org/wiki/NTU_RGB-D_dataset

    The NTU RGB-D (Nanyang Technological University's Red Blue Green and Depth information) dataset is a large dataset containing recordings of labeled human activities. [1] This dataset consists of 56,880 action samples containing 4 different modalities (RGB videos, depth map sequences, 3D skeletal data, infrared videos) of data for each sample.

  3. List of datasets in computer vision and image processing

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

    ~60 million Images, text Object recognition, scene recognition 2015 [20] [21] [22] Yu et al. Open Images A Large set of images listed as having CC BY 2.0 license with image-level labels and bounding boxes spanning thousands of classes. Image-level labels, Bounding boxes 9,178,275 Images, text Classification, Object recognition 2017 (V7 : 2022) [23]

  4. Category:Datasets in computer vision - Wikipedia

    en.wikipedia.org/wiki/Category:Datasets_in...

    NTU RGB-D dataset; O. ... This page was last edited on 5 May 2023, at 16:13 (UTC). Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; ...

  5. Bayer filter - Wikipedia

    en.wikipedia.org/wiki/Bayer_filter

    Full RGB version at 120×80-pixels for comparison (e.g. as a film scan, Foveon or pixel shift image might appear) Bryce Bayer 's patent (U.S. Patent No. 3,971,065 [ 6 ] ) in 1976 called the green photosensors luminance-sensitive elements and the red and blue ones chrominance-sensitive elements .

  6. MNIST database - Wikipedia

    en.wikipedia.org/wiki/MNIST_database

    The set of images in the MNIST database was created in 1994. Previously, NIST released two datasets: Special Database 1 (NIST Test Data I, or SD-1); and Special Database 3 (or SD-2). They were released on two CD-ROMs. SD-1 was the test set, and it contained digits written by high school students, 58,646 images written by 500 different writers.

  7. 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]

  8. Talk:NTU RGB-D dataset - Wikipedia

    en.wikipedia.org/wiki/Talk:NTU_RGB-D_dataset

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  9. Comparison of color models in computer graphics - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_color_models...

    In the RGB model, hues are represented by specifying one color as full intensity (255), a second color with a variable intensity, and the third color with no intensity (0). The following provides some examples using red as the full-intensity and green as the partial-intensity colors; blue is always zero: