articleApr 12, 2005Closed access
Best practices for convolutional neural networks applied to visual document analysis
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Abstract
Neural networks are a powerful technology forclassification of visual inputs arising from documents.However, there is a confusing plethora of different neuralnetwork methods that are used in the literature and inindustry. This paper describes a set of concrete bestpractices that document analysis researchers can use toget good results with neural networks. The mostimportant practice is getting a training set as large aspossible: we expand the training set by adding a newform of distorted data. The next most important practiceis that convolutional neural networks are better suited forvisual document tasks than fully connected networks. Wepropose that a simple do-it-yourself implementation ofconvolution with a…
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Keywords
- MNIST database
- Convolutional neural network
- Computer science
- Set (abstract data type)
- Simple (philosophy)
- Architecture
- Artificial neural network
- Artificial intelligence
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