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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]
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.
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 ...
Microsoft 365 is a family of productivity software, collaboration and cloud-based services, encompassing online services, products formerly marketed under Microsoft Office, and enterprise products and services. This list contains all the programs that are, or have been, in Microsoft Office since it was released for classic Mac OS in 1989, and ...
Database with images of 131 fruits and vegetables. 100x100 pixels, white background. 90483 Images (jpg) Classification 2017–2024 [318] Mihai Oltean Weed-ID.App Database with 1,025 species, 13,500+ images, and 120,000+ characteristics Varying size and background. Labeled by PhD botanist. 13,500 Images, text Classification 1999-2024 [319 ...
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.
Yann André Le Cun [1] (/ l ə ˈ k ʌ n / lə-KUN, French:; [2] usually spelled LeCun; [2] born 8 July 1960) is a French-American computer scientist working primarily in the fields of machine learning, computer vision, mobile robotics and computational neuroscience.
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