http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-110232314-A

Outgoing Links

Predicate Object
assignee http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_6fbb91e3f8cdf858527814216aa11142
classificationCPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-2411
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06V40-103
classificationIPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62
filingDate 2019-04-28-04:00^^<http://www.w3.org/2001/XMLSchema#date>
inventor http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_cf63de727c632046f5fd460b8e1d6aa1
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_fb80aebf37e46a67caeaac1d8acae8b7
publicationDate 2019-09-13-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber CN-110232314-A
titleOfInvention An image pedestrian detection method based on improved Hog feature combined with neural network
abstract The invention discloses an image pedestrian detection method based on an improved Hog feature combined with a neural network. The image pixel gradient is calculated by using a directional controllable filter algorithm to improve the operation rate. In addition, when detecting pedestrians, instead of using a fixed window to slide the entire image for detection, the frame difference method is used to determine the motion area first, and the motion area is scaled to a certain extent, and the detection is performed in the area to reduce the computational cost. time and improve detection efficiency.
isCitedBy http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-113163110-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-113163110-B
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-112488039-A
priorityDate 2019-04-28-04:00^^<http://www.w3.org/2001/XMLSchema#date>
type http://data.epo.org/linked-data/def/patent/Publication

Incoming Links

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isDiscussedBy http://rdf.ncbi.nlm.nih.gov/pubchem/substance/SID419474851
http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID21855

Total number of triples: 19.