| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_08fa68111c9d2a13e1efa3fa1ad1cf9f |
| classificationCPCAdditional |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30148
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30204
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20084
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20081 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-136
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-241
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/G06T7-13
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T5-30 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-13
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T5-30
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-04
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-136 |
| filingDate |
2021-06-04-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_7f5ad17e4f208fe25f9611653d36fa1b
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_d2e8888e23bc6e643e2d9df46af80d5b |
| publicationDate |
2021-10-26-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
CN-113554054-A |
| titleOfInvention |
Method and system for classification of semiconductor chip gold wire defects based on deep learning |
| abstract |
The present invention provides a method and system for classifying gold wire defects of semiconductor chips based on deep learning, including: using a light field camera to photograph the chip to obtain a central perspective map and depth information, and each of the central perspective maps includes two complete chips ; segment the center view image to obtain a grayscale image of a single chip; mark the outlines of the gold lines of the grayscale image of the single chip respectively; carry out defect classification on the grayscale image after the marked contour in combination with the depth information, and obtain Datasets; use the datasets for gold wire defect classification on semiconductor chip drawings. The present invention has a high accuracy rate in the test set, and can effectively determine the three kinds of defects of the gold wire and the intact category characteristics. |
| isCitedBy |
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-115375679-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-110598815-B
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-110598815-A |
| priorityDate |
2021-06-04-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |