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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.
Linnaeus 5 dataset Images of 5 classes of objects. Classes labelled, training set splits created. 8000 Images Classification 2017 [40] Chaladze & Kalatozishvili 11K Hands 11,076 hand images (1600 x 1200 pixels) of 190 subjects, of varying ages between 18 – 75 years old, for gender recognition and biometric identification. None 11,076 hand images
NTU RGB-D dataset; O. Overhead Imagery Research Data Set; T. Textures: A Photographic Album for Artists and Designers ... This page was last edited on 5 May 2023, at ...
Car Evaluation Data Set Car properties and their overall acceptability. Six categorical features given. 1728 Text Classification 1997 [13] [14] M. Bohanec YouTube Comedy Slam Preference Dataset User vote data for pairs of videos shown on YouTube. Users voted on funnier videos. Video metadata given. 1,138,562 Text Classification 2012 [15] [16 ...
Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
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.
In 15-bit high color, one of the bits of the two bytes is ignored or set aside for an alpha channel, and the remaining 15 bits are split between the red, green, and blue components of the final color. Each of the RGB components has 5 bits associated, giving 2⁵ = 32 intensities of each component. This allows 32768 possible colors for each pixel.
The CIFAR-10 dataset (Canadian Institute For Advanced Research) is a collection of images that are commonly used to train machine learning and computer vision algorithms. It is one of the most widely used datasets for machine learning research. [1] [2] The CIFAR-10 dataset contains 60,000 32x32 color images in 10 different classes. [3]