| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_fcb78cf23054a23ceb0c657957b8212d |
| classificationCPCAdditional |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N2021-8887
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20081 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N21-8851
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-13
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-241
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-12
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-045
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-08
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-0008 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-04
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-12
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-13
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01N21-88
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V10-764 |
| filingDate |
2021-12-10-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_41d8e7d873f545fc486c977daade8150
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_bc6386cd82a2136f619b9a06a34b871f
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_4cb7403cf9cc232b9d8906b8abe1e7e1
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_46e9021a19f9bf9def50bee3b6f30d5c
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_f1bd5aa2b28366abd9bc84fb0d4021f5
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_54cd4b7707c81310d83b7f714e3e5eb7 |
| publicationDate |
2022-03-18-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
CN-114202525-A |
| titleOfInvention |
A detection method for intelligent manufacturing products based on machine vision |
| abstract |
The invention relates to the field of defect detection, in particular to a method for detecting intelligent manufacturing products based on machine vision; S1: acquiring training samples and preprocessing the training samples to obtain training sample data; S2: based on multiple convolution layers and pooling layer to build a custom image segmentation network and train the custom image segmentation network according to the training sample data to obtain the trained segmentation network; S3: build a custom image decision network based on the last convolutional layer and global max pooling and according to the training samples The data is used to train the self-defined image decision network, and the trained decision network is obtained; S4: Based on the trained segmentation network and the trained decision network, the sample to be tested is detected, and the detection result is obtained. The invention provides an intelligent manufacturing product detection method based on machine vision, which has the advantages of reducing cost, improving product quality and being suitable for various industrial product defect detection scenarios. |
| priorityDate |
2021-12-10-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |