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Includes Handwritten Numeral Dataset (10 classes) and Basic Character Dataset (50 classes), each dataset has three types of noise: white gaussian, motion blur, and reduced contrast. All images are centered and of size 32x32. Numeral Dataset: 23330, Character Dataset: 76000 Images, text Handwriting recognition, classification 2017 [145] [146]
The datasets are classified, based on the licenses, as Open data and Non-Open data. The datasets from various governmental-bodies are presented in List of open government data sites. The datasets are ported on open data portals. They are made available for searching, depositing and accessing through interfaces like Open API. The datasets are ...
The LabelMe project provides a set of tools for using the LabelMe dataset from Matlab. Since research is often done in Matlab, this allows the integration of the dataset with existing tools in computer vision. The entire dataset can be downloaded and used offline, or the toolbox allows dynamic downloading of content on demand.
Extended MNIST (EMNIST) is a newer dataset developed and released by NIST to be the (final) successor to MNIST. [ 15 ] [ 16 ] MNIST included images only of handwritten digits. EMNIST includes all the images from NIST Special Database 19 (SD 19), which is a large database of 814,255 handwritten uppercase and lower case letters and digits.
The Caltech 101 data set was used to train and test several computer vision recognition and classification algorithms. The first paper to use Caltech 101 was an incremental Bayesian approach to one-shot learning, [ 4 ] an attempt to classify an object using only a few examples, by building on prior knowledge of other classes.
Training, validation, and test data sets This page was last edited on 5 May 2023, at 21:06 (UTC). Text is available under the Creative Commons Attribution ...
Two years after finally being identified, the "Boy in the Box" case continues to haunt Philadelphia. The slain body of Joseph Augustus Zarelli, 4, was discovered in February 1957 in Philadelphia's ...
FERG-3D-DB (Facial Expression Research Group 3D Database) for stylized characters [3] angry, disgust, fear, joy, neutral, sad, surprise 4 39574 annotated examples Color Emotion labels Frontal pose Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) [4] Speech: Calm, happy, sad, angry, fearful, surprise, disgust, and neutral.