METHOD AND APPARATUS FOR MULTI-LABEL CLASS CLASSIFICATION BASED ON COARSE-TO-FINE CONVOLUTIONAL NEURAL NETWORK

An apparatus for multi-label class classification based on a coarse-to-fine convolutional neural network includes: a processor; and a memory connected to the processor, in which the memory stores program instructions executed by the processor to generate a plurality of hierarchical structure based g...

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Bibliographic Details
Main Authors SHIN, Min Woo, PARK, Jin Ho, PAIK, Joon Ki, KIM, Hee Gwang
Format Patent
LanguageEnglish
Published 05.09.2024
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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Summary:An apparatus for multi-label class classification based on a coarse-to-fine convolutional neural network includes: a processor; and a memory connected to the processor, in which the memory stores program instructions executed by the processor to generate a plurality of hierarchical structure based group labels for a plurality of classes to be classified by using a disjoint grouping method, predict classes which belong to the plurality of group labels, respectively among the plurality of classes by using a coarse-to-fine convolutional neural network including a main network and one or more subnetworks, complete learning of the coarse-to-fine convolutional network through the prediction, and classify one or more classes included in the image by receiving a feature map input from a last convolutional layer of the one or more subnetworks by the main network of the coarse-to-fine convolutional neural network of which learning is completed.
Bibliography:Application Number: US202418659042