Multi-Column Deep Neural Networks for offline handwritten Chinese character classification

Autor:	Ueli Meier, Dan Ciresan
Rok vydání:	2015
Předmět:	CUDA Kernel (image processing) business.industry Computer science Handwriting Chinese character classification Deep neural networks Pattern recognition Artificial intelligence Graphics Overfitting Chinese characters business
Zdroj:	IJCNN
Popis:	Multi-Column Deep Neural Networks achieve state of the art recognition rates on Chinese characters from the ICDAR 2011 and 2013 offline handwriting competitions, approaching human accuracy. This performance is the result of averaging 11-layers deep networks with hundreds of maps per layer, trained on raw, distorted images to prevent them from overfitting. The entire framework runs on a normal desktop computer with a CUDA capable graphics card.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::6df471276512d30081257b3f575ea624 https://doi.org/10.1109/ijcnn.2015.7280516 Zobrazit plný text záznamu