http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-111461990-B
Outgoing Links
| Predicate | Object |
|---|---|
| classificationCPCAdditional | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20081 |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-10 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T3-4053 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T3-40 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-10 |
| filingDate | 2020-04-03-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate | 2022-03-18-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationDate | 2022-03-18-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-111461990-B |
| titleOfInvention | Method for realizing super-resolution imaging step by step based on deep learning |
| abstract | The invention discloses a method for realizing super-resolution imaging step by step based on deep learning, which comprises the following steps: s1, inputting the low-resolution image to be processed into a pre-trained neural network to obtain an intermediate-resolution image; s2, cutting the intermediate resolution image after amplifying the intermediate resolution image by k times to ensure that the resolution of the intermediate resolution image is matched with the resolution of the low resolution image to be processed; wherein k is the ratio of the pixel resolution of the low-resolution image to be processed to the pixel resolution of the intermediate-resolution image; and S3, sequentially inputting the cut images into the pre-trained neural network, splicing the obtained images according to the original cutting sequence, and reducing the spliced images to the original 1/k to obtain high-resolution images. According to the invention, by improving the resolution of the image in a blocking and step-by-step manner, the problem of low performance of a neural network for image conversion caused by overlarge difference between a low-resolution image and a high-resolution image is solved, and the obtained super-resolution image has a good effect. |
| priorityDate | 2020-04-03-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
| Predicate | Subject |
|---|---|
| isDiscussedBy | http://rdf.ncbi.nlm.nih.gov/pubchem/substance/SID419481065 http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID5601 |
Total number of triples: 17.