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Sample images from MNIST test dataset. The MNIST database (Modified National Institute of Standards and Technology database [1]) is a large database of handwritten digits that is commonly used for training various image processing systems. [2] [3] The database is also widely used for training and testing in the field of machine learning.
MNIST: Database of grayscale handwritten digits. 60,000 image, label classification 1994 [1] LeCun et al. Extended MNIST: Database of grayscale handwritten digits and letters. 810,000 image, label classification 2010 [2] NIST 80 Million Tiny Images: 80 million 32×32 images labelled with 75,062 non-abstract nouns. 80,000,000 image, label 2008 [3]
Recognizing simple digit images is the most classic application of LeNet as it was created because of that. Yann LeCun et al. created LeNet-1 in 1989. The paper Backpropagation Applied to Handwritten Zip Code Recognition [4] demonstrates how such constraints can be integrated into a backpropagation network through the architecture of the ...
The MNIST database is created to train machine learning models in pattern recognition. [27] 2015 Application Open access Google offers OCR tools to scan any Google Drive files in over 200 languages for free. [6]
Video of the process of scanning and real-time optical character recognition (OCR) with a portable scanner. Optical character recognition or optical character reader (OCR) is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene photo (for example the text on signs and ...
Signature of country star Tex Williams. Handwriting recognition (HWR), also known as handwritten text recognition (HTR), is the ability of a computer to receive and interpret intelligible handwritten input from sources such as paper documents, photographs, touch-screens and other devices.
A common evaluation set for image classification is the MNIST database data set. MNIST is composed of handwritten digits and includes 60,000 training examples and 10,000 test examples. As with TIMIT, its small size lets users test multiple configurations. A comprehensive list of results on this set is available. [185]
Free Music Archive: Audio under Creative Commons from 100k songs (343 days, 1TiB) with a hierarchy of 161 genres, metadata, user data, free-form text. Raw audio and audio features. 106,574 Text, MP3 Classification, recommendation 2017 [143] M. Defferrard et al. Bach Choral Harmony Dataset Bach chorale chords. Audio features extracted. 5665 Text