Ragewa da Rushe hanyoyin sadarwa
Ƙwarewa da ɓarna cibiyoyin sadarwa nau'ikan jijiyoyi ne waɗanda ke share hotuna masu surutu ko blur, suna dawo da dalla-dalla daga abubuwan da ba su da kyau.
Dubawa
They matter because nearly every camera, phone, and medical scanner produces imperfect images that these networks can rescue.
Zurfafa nutsewa
Karɓatawa yana cire bazuwar hatsi (sau da yawa daga ƙaramin haske ko babban ISO), yayin da ɓarna ke juyar da ɓarnar da girgizar kamara ta haifar, motsi, ko rashin mayar da hankali. Dukansu ayyuka ne na 'mayar da hoto' inda cibiyar sadarwa ke koyon taswira daga lalataccen hoto zuwa mai tsabta. Tsarin zurfafa na gargajiya kamar DnCNN ya koyi tsinkayar amo da kansa, sannan a cire shi, yayin da daga baya aikin yayi amfani da U-Net encoder-decoders waɗanda ke damfara da sake gina hotuna. Deblurring ya fi wuya saboda blur 'kernel' (yadda kowane pixel ya sami shafa) yawanci ba a san shi ba, don haka makafi masu lalata hanyoyin sadarwa dole ne su kimanta duka kwaya da hoto mai kaifi. Ana yin nau'i-nau'i na horarwa ta hanyar ƙara hayaniya ko blur don tsaftace hotuna don cibiyar sadarwa ta ga amsar daidai.
Fahimtar Fasaha
Yawancin masu karyatawa suna amfani da ragowar koyo: maimakon tsinkayar hoto mai tsabta kai tsaye, DnCNN ya annabta ragowar karar kuma ya rage shi, wanda ya fi sauƙi don ingantawa. Deblurring sau da yawa yana amfani da ma'auni da yawa ko ƙira mai maimaitawa waɗanda ke tace hoton da kyau-zuwa-lafiya. Ayyukan hasara sun haɗa kuskuren pixel (L1/L2) tare da hasashe na fahimta ko gaba don haka sakamakon ya yi kama da na halitta maimakon fiye da laushi. Dabarun kulawa da kai kamar Noise2Noise har ma da horarwa ba tare da tsaftataccen manufa ba ta hanyar zana firam ɗin hayaniya zuwa wani.
Dabarun Tasiri
Gudu da sikelin
Kayayyakin AI na iya sarrafa aiki da bincike, ganowa, da ayyuka masu alama a sikelin.
Gina zaɓuɓɓuka
Ƙungiyoyin ƙirƙira za su iya samar da ra'ayoyi cikin sauri tare da ƙarancin bita da hannu.
Ƙungiya da aikin aiki
Ayyuka na iya amfani da siginar hoto da bidiyo waɗanda a baya suke da wahalar aiwatarwa.
Makomar Ƙarfafawa da Rushe hanyoyin sadarwa
Masu dawo da tushen watsawa suna zama sabon ma'auni, suna kula da ƙididdigewa a matsayin ginshiƙan samfurin ƙirƙira da kuma samar da kintsattse, kayan laushi na gaske. Ma'auni na ɓarna na ainihi (ba kawai na roba ba) kamar SIDD suna tura samfuran zuwa hayaniyar kyamara ta gaske. Yi tsammanin kan na'urar, maidowa na ainihin lokacin da aka gasa cikin ISPs na waya da kiran bidiyo, da samfuran 'duk-in-daya' waɗanda ke ɗaukar amo, blur, ruwan sama, da hazo tare. Iyakar tana daidaita murmurewa daki-daki daki-daki da natsuwa mai ruɗi wanda bai taɓa can ba.
Aiwatar da Gaskiyar Duniya
Yanayin dare na wayowin komai da ruwan ka tare da hana firam masu duhu da yawa cikin hoto mai ƙarancin haske mai tsafta
Cire blur motsi daga faranti ko fuskoki cikin tsaro da faifan bincike
Tsaftace hatsi da kayan tarihi na matsawa daga tsohon ko ƙaramin bidiyo mai ƙarancin bitar kafin yawo
Rage amo a cikin ƙananan CT da MRI scans don haka likitoci zasu iya rage radiation yayin kiyaye daki-daki
Hatsari & Tsare-tsare
Haƙƙoƙin hoto da yarda na iya zama haxarin doka idan ba a fayyace ba.
Ayyukan samfuri na iya bambanta a ko'ina cikin haske, ƙididdiga, da mahalli.
Ƙarya tabbataccen ƙila ba za a iya lura da shi ba sai dai idan an kula da ƙofofin amincewa.
Taswirar Hanya
Ƙayyade ma'auni na karɓa don daidaito, tunowa, da farashi na kuskure.
Gwada tare da bayanan da suka dace da ainihin yanayin samarwa.
Ƙara bita na ɗan adam don ƙarancin amincewa ko tsinkaya mai tasiri.
Bi diddigin ƙirar ƙira kuma sake ingantawa bayan canje-canjen kamara ko saitin bayanai.
Ci gaba da Bincike
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Jagora na gaba
Ragowar hanyoyin sadarwa
Tambayoyin da ake yawan yi
What is Denoising and Deblurring Networks?
Ƙwarewa da ɓarna cibiyoyin sadarwa nau'ikan jijiyoyi ne waɗanda ke share hotuna masu surutu ko blur, suna dawo da dalla-dalla daga abubuwan da ba su da kyau. Suna da mahimmanci saboda kusan kowace kyamara, waya, da na'urar daukar hotan takardu na likita suna samar da cikakkun hotuna waɗanda waɗannan cibiyoyin sadarwa zasu iya ceto.
Menene ainihin DnCNN ya annabta yayin horo?
DnCNN yana amfani da ragowar koyo, yana tsinkayar amo da kansa don a iya rage shi, wanda ya fi sauƙi fiye da sake gina dukkan hoto mai tsabta.
Me ya sa aka ɗauki ɓarna makaho da wahala fiye da ƙin yarda?
A cikin ɓarna makaho dole ne hanyar sadarwa ta ƙiyasta kernel ɗin da ba a sani ba da kuma hoton da ba a sani ba a lokaci guda, mai da shi matsala mara kyau.
Ta yaya ake ƙirƙira nau'ikan horarwa don waɗannan cibiyoyin sadarwa?
Masu bincike suna ƙasƙantar da hotuna masu tsafta tare da surutu da aka kwaikwayi ko blur don haka hanyar sadarwar ta sami daidaitaccen manufa mai tsabta don koyo daga gare ta.
Menene gine-ginen da aka fi amfani dashi azaman kashin baya don maido da hoto?
U-Net style encoder-decoders damfara sa'an nan sake gina hoton tare da tsallake hanyoyin da ke adana daki-daki, sa su shahara don maidowa.
Menene mabuɗin ra'ayin da ke bayan tsarin horarwar Noise2Noise?
Noise2Noise yana nuna cewa zaku iya horar da mai karyatawa ta amfani da nau'ikan hotuna masu hayaniya, tunda cibiyar sadarwa tana koyon siginar tsaftar da ke cikin sa rai.