METHOD, APPARATUS, ELECTRONIC DEVICE AND MEDIUM FOR IMAGE SUPER-RESOLUTION AND MODEL TRAINING
The embodiments of the present application provide method, apparatus, electronic device, and medium for image super-resolution and model training. The method includes: inputting the image to be processed into a first super-resolution network model and a second super-resolution network model trained...
Gespeichert in:
| Hauptverfasser: | , , , |
|---|---|
| Format: | Patent |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | |
| container_start_page | |
| container_title | |
| container_volume | |
| creator | WANG, Xian FAN, Hongfei LU, Fangbo CAI, Yuan |
| description | The embodiments of the present application provide method, apparatus, electronic device, and medium for image super-resolution and model training. The method includes: inputting the image to be processed into a first super-resolution network model and a second super-resolution network model trained in advance, respectively; the first super-resolution network model is a trained convolutional neural network; the second super-resolution network model is a generative network included in a trained generative adversarial network; obtaining a first image output from the first super-resolution network model and a second image output from the second super-resolution network model; fusing the first image and the second image to obtain a target image, wherein the resolution of the target image is greater than the resolution of the image to be processed. |
| format | Patent |
| fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_US2022383452A1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>US2022383452A1</sourcerecordid><originalsourceid>FETCH-epo_espacenet_US2022383452A13</originalsourceid><addsrcrecordid>eNqNyjsKwkAQANA0FqLeYcA2Ad0YsB12J8nAfsJ-7CQEWSvRQLw_FnoAq9e8dXE1FHunSsBhQI8xhRJIk4zeWZag6MKSAK0CQ4qTgdZ5YIMdQUgD-cpTcDpFdva7nCIN0SNbtt22WN2nx5J3PzfFvqUo-yrPrzEv83TLz_weUxAHIepzfWoEHuv_1geIkTNG</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>METHOD, APPARATUS, ELECTRONIC DEVICE AND MEDIUM FOR IMAGE SUPER-RESOLUTION AND MODEL TRAINING</title><source>esp@cenet</source><creator>WANG, Xian ; FAN, Hongfei ; LU, Fangbo ; CAI, Yuan</creator><creatorcontrib>WANG, Xian ; FAN, Hongfei ; LU, Fangbo ; CAI, Yuan</creatorcontrib><description>The embodiments of the present application provide method, apparatus, electronic device, and medium for image super-resolution and model training. The method includes: inputting the image to be processed into a first super-resolution network model and a second super-resolution network model trained in advance, respectively; the first super-resolution network model is a trained convolutional neural network; the second super-resolution network model is a generative network included in a trained generative adversarial network; obtaining a first image output from the first super-resolution network model and a second image output from the second super-resolution network model; fusing the first image and the second image to obtain a target image, wherein the resolution of the target image is greater than the resolution of the image to be processed.</description><language>eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ; PHYSICS</subject><creationdate>2022</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20221201&DB=EPODOC&CC=US&NR=2022383452A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20221201&DB=EPODOC&CC=US&NR=2022383452A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>WANG, Xian</creatorcontrib><creatorcontrib>FAN, Hongfei</creatorcontrib><creatorcontrib>LU, Fangbo</creatorcontrib><creatorcontrib>CAI, Yuan</creatorcontrib><title>METHOD, APPARATUS, ELECTRONIC DEVICE AND MEDIUM FOR IMAGE SUPER-RESOLUTION AND MODEL TRAINING</title><description>The embodiments of the present application provide method, apparatus, electronic device, and medium for image super-resolution and model training. The method includes: inputting the image to be processed into a first super-resolution network model and a second super-resolution network model trained in advance, respectively; the first super-resolution network model is a trained convolutional neural network; the second super-resolution network model is a generative network included in a trained generative adversarial network; obtaining a first image output from the first super-resolution network model and a second image output from the second super-resolution network model; fusing the first image and the second image to obtain a target image, wherein the resolution of the target image is greater than the resolution of the image to be processed.</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2022</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNyjsKwkAQANA0FqLeYcA2Ad0YsB12J8nAfsJ-7CQEWSvRQLw_FnoAq9e8dXE1FHunSsBhQI8xhRJIk4zeWZag6MKSAK0CQ4qTgdZ5YIMdQUgD-cpTcDpFdva7nCIN0SNbtt22WN2nx5J3PzfFvqUo-yrPrzEv83TLz_weUxAHIepzfWoEHuv_1geIkTNG</recordid><startdate>20221201</startdate><enddate>20221201</enddate><creator>WANG, Xian</creator><creator>FAN, Hongfei</creator><creator>LU, Fangbo</creator><creator>CAI, Yuan</creator><scope>EVB</scope></search><sort><creationdate>20221201</creationdate><title>METHOD, APPARATUS, ELECTRONIC DEVICE AND MEDIUM FOR IMAGE SUPER-RESOLUTION AND MODEL TRAINING</title><author>WANG, Xian ; FAN, Hongfei ; LU, Fangbo ; CAI, Yuan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US2022383452A13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2022</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>WANG, Xian</creatorcontrib><creatorcontrib>FAN, Hongfei</creatorcontrib><creatorcontrib>LU, Fangbo</creatorcontrib><creatorcontrib>CAI, Yuan</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>WANG, Xian</au><au>FAN, Hongfei</au><au>LU, Fangbo</au><au>CAI, Yuan</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>METHOD, APPARATUS, ELECTRONIC DEVICE AND MEDIUM FOR IMAGE SUPER-RESOLUTION AND MODEL TRAINING</title><date>2022-12-01</date><risdate>2022</risdate><abstract>The embodiments of the present application provide method, apparatus, electronic device, and medium for image super-resolution and model training. The method includes: inputting the image to be processed into a first super-resolution network model and a second super-resolution network model trained in advance, respectively; the first super-resolution network model is a trained convolutional neural network; the second super-resolution network model is a generative network included in a trained generative adversarial network; obtaining a first image output from the first super-resolution network model and a second image output from the second super-resolution network model; fusing the first image and the second image to obtain a target image, wherein the resolution of the target image is greater than the resolution of the image to be processed.</abstract><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | |
| ispartof | |
| issn | |
| language | eng |
| recordid | cdi_epo_espacenet_US2022383452A1 |
| source | esp@cenet |
| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING IMAGE DATA PROCESSING OR GENERATION, IN GENERAL PHYSICS |
| title | METHOD, APPARATUS, ELECTRONIC DEVICE AND MEDIUM FOR IMAGE SUPER-RESOLUTION AND MODEL TRAINING |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-23T09%3A55%3A54IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=WANG,%20Xian&rft.date=2022-12-01&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3EUS2022383452A1%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |