SignMNIST
OpenML dataset with id 45082
Author name not available (Why is that?)
Full work available at URL: https://api.openml.org/data/v1/download/22112117/SignMNIST.arff
Upload date: 9 February 2023
Dataset Characteristics
Number of classes: 0
Number of features: 785 (numeric: 785, symbolic: 0 and in total binary: 0 )
Number of instances: 34,627
Number of instances with missing values: 0
Number of missing values: 0
The original MNIST image dataset of handwritten digits is a popular benchmark for image-based machine learning methods but researchers have renewed efforts to update it and develop drop-in replacements that are more challenging for computer vision and original for real-world applications.
The dataset format is patterned to match closely with the classic MNIST. Each training and test case represents a label (0-25) as a one-to-one map for each alphabetic letter A-Z (and no cases for 9=J or 25=Z because of gesture motions). The training data (27,455 cases) and test data (7172 cases) are approximately half the size of the standard MNIST but otherwise similar with a header row of label, pixel1, pixel2 ... pixel784 which represent a single 28x28 pixel image with grayscale values between 0-255.
The train and test data have been concatenated and can be retrieved by selecting the first 27,455 rows for train and the last 7172 for test.
This page was built for dataset: SignMNIST
