http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-106682736-A

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assignee http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_ac242e63c7b998ac371691bd9437cf33
classificationCPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-084
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-00
classificationIPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-00
filingDate 2017-01-18-04:00^^<http://www.w3.org/2001/XMLSchema#date>
inventor http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_9e4a937338798c2dbe2be6c9e8077a7c
publicationDate 2017-05-17-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber CN-106682736-A
titleOfInvention Image recognition method and device
abstract The present disclosure relates to an image recognition method and device. The method includes: inputting the image to be recognized into a trained first convolutional neural network, the first convolutional neural network includes P groups of convolutional layers, each group of convolutional layers includes two convolutional layers, and the two The convolution kernels of the convolution layer are respectively the first convolution kernel with a size of 1*N and the second convolution kernel with a size of N*1; through each group of convolution layers of the first convolution neural network pair The image to be recognized is subjected to feature extraction to obtain the features to be extracted of each set of convolutional layers; the recognition result of the image to be recognized is determined according to the features to be extracted of each set of convolutional layers. The technical solution provided by the present disclosure solves the problems of large calculation amount and high calculation cost caused by adopting a square convolution kernel in the related art.
isCitedBy http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-10699160-B2
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-109784186-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-111798520-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-107967459-B
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/WO-2019105243-A1
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-109033940-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-107943750-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-107944545-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-107944545-B
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-109840584-B
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-10909418-B2
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-109978137-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-107967459-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-109978137-B
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-111247527-A
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priorityDate 2017-01-18-04:00^^<http://www.w3.org/2001/XMLSchema#date>
type http://data.epo.org/linked-data/def/patent/Publication

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Total number of triples: 31.