HANDWRITING RECOGNITION

A simplified handwriting recognition approach includes a first network comprising convolutional neural network comprising one or more convolutional layers and one or more max-pooling layers. The first network receives an input image of handwriting and outputs an embedding based thereon. A second net...

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Bibliographic Details
Main Authors YU, Yen-Yun, DEY, Raunak, VENI, Gopalkrishna Balkrishna, FUJIMOTO, Masaki Stanley, LEE, Jinsol
Format Patent
LanguageEnglish
French
German
Published 18.10.2023
Subjects
CALCULATING
COMPUTING
COUNTING
PHYSICS
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Summary:A simplified handwriting recognition approach includes a first network comprising convolutional neural network comprising one or more convolutional layers and one or more max-pooling layers. The first network receives an input image of handwriting and outputs an embedding based thereon. A second network comprises a network of cascaded convolutional layers including one or more subnetworks configured to receive an embedding of a handwriting image and output one or more character predictions. The subnetworks are configured to downsample and flatten the embedding to a feature map and then a vector before passing the vector to a dense neural network for character prediction. Certain subnetworks are configured to concatenate an input embedding with an upsampled version of the feature map.
Bibliography:Application Number: EP20210840272