Hagaha AI ee Muuqaalka

Shabakadaha Hadhaaga ah

Shabakadaha Hadhaaga ah (ResNets) waa shabakado neerfaha qoto dheer oo ku dara 'isku-xidhka ka boodka' taasoo u oggolaanaysa lakabyada inay bartaan hagaajin yar halkii ay ka beddeli lahaayeen isbeddel buuxa.

2 daqiiqo akhriMarkii u dambaysay ee la cusbooneysiiyay

Dulmar

This simple trick made it possible to train networks hundreds of layers deep, sparking a leap in image recognition accuracy.

quusid qoto dheer

Kahor ResNets, isku xidhka lakabyo badan oo shabakadaha si aan caadi ahayn u sameeyay ayaa kasii xun, xitaa xogta tababarka, dhibaatada loo yaqaan hoos u dhaca. Sannadkii 2015, Microsoft cilmi-baarayaasha Kaiming He iyo asxaabtiisu waxay soo bandhigeen xannibaadda haraaga ah: halkii ay ka weydiin lahaayeen xirmo lakab ah si ay u soo saaraan wax soo saarka H (x) si toos ah, waxay u oggolaadaan inay bartaan haraaga F(x) = H (x) - x, ka dibna waxay ku daraan gelinta asalka ah x dib iyada oo loo marayo qaab gaaban. Haddii lakabka aan loo baahnayn, waxay si fudud u baran kartaa inaan waxba samayn (F(x) = 0). ResNet-152 waxay ku guulaysatay tartankii ImageNet 2015 iyadoo qaladka ugu sarreeya ee 5 ku saabsan yahay 3.6 boqolkiiba, garaacday qiyaasaha heerka bini'aadamka, iyo qaabdhismeedkeedu wuxuu noqday laf dhabarta aasaasiga ah ee ogaanshaha, qaybinta, iyo sawirka caafimaadka.

Aragtida Farsamada

Xidhiidhka boodboodku waxa uu shaqadiisa block u rogaa y = F(x) + x. Inta lagu jiro faafinta, gradient-ku wuxuu dhex maraa marin-gaaban aqoonsiga isma beddelin, markaa ma lumin karo meel u dhow xitaa boqolaal lakab. Tani waxay ilaalinaysaa xirmooyinka qoto dheer ee la tababari karo. Jid-gaabyada aqoonsiga ma ku darayaan cabbiro dheeraad ah; Kaliya marka cabbirka wax-gelinta iyo wax-soo-saarka ay kala duwan yihiin ayaa qiyaas yar (1x1 convolution) hagaajiyaa cabbirrada ka hor isku-darka.

Saamaynta Istiraatijiyadeed

Xawaaraha iyo miisaanka

Visual AI wuxuu si otomaatig ah u samayn karaa baadhista, ogaanshaha, iyo sumadaynta hawlaha miisaanka.

Xulashada dhismayaasha

Kooxaha hal-abuurka leh waxay hindise karaan fikradaha si dhakhso leh iyagoo leh dib-u-eegis buugeed yar.

Kooxda iyo socodka shaqada

Hawlgalladu waxay isticmaali karaan calaamadaha muuqaalka iyo muuqaalka kuwaas oo markii hore adkeyd in la farsameeyo.

Mustaqbalka Shabakadaha Hadhaaga ah

Xidhiidhada haraaga ah hadda waa u dhow yihiin caalim: Transformers, moodooyinka faafinta, iyo moodooyinka luqadaha waaweyn dhamaantood waxay isticmaalaan si ay u dejiyaan tababarka xirmooyinka aadka u qoto dheer. Cilmi-baadhistu waxay ku sii socotaa kala duwanaanshaha sida ResNets-ka-hor-u-gelinta, waddooyinka ResNeXt ee kooxaysan, iyo isku-darka fikradaha haraaga ah iyo tababbarka caadiga ah ee bilaashka ah. Filo in mabda'a isku xidhka boodada ee udub-dhexaadka ah uu u sii ahaado dhisme aan caadi ahayn, xitaa marka dhismayaasha ku hareeraysan ay ka weecanayaan isfahamka saafiga ah ee dareenka iyo naqshadaha isku dhafan.

Dhaqangelinta Adduunka-dhabta ah

Laf-dhabarta kala soocidda ImageNet (ResNet-50, ResNet-101) oo loo isticmaalo soosaarayaal sifo hore loo tababaray oo loogu talagalay wareejinta barashada

Ogaanshaha burada iyo nabarka ee shucaaca iyo sawirada pathology iyadoo la isticmaalayo codeerayaal ku saleysan ResNet

Ogaanshaha shayga iyo tusaale ahaan qaabdhismeedka qaybinta sida Degdega R-CNN iyo Maaskarada R-CNN ee adeegsada laf dhabarta ResNet

Dhuumaha is-wadda garashada ee kala saara dadka lugeynaya, baabuurta, iyo calamadaha kaamirooyinka

Khatarta & Dariiqyada Ilaalada

Xuquuqda sawirka iyo ogolaanshaha waxay noqon kartaa khataro sharci ah haddii caddayntu aanay caddayn.

Waxqabadka moodeelku wuu ku kala duwanaan karaa iftiinka, tirakoobka, iyo deegaanka.

Wanaagga beenta ah waxa laga yaabaa inaan la dareemin ilaa xadka kalsoonida aan la kormeerin.

Qorshe Hawleedka Dhaqangelinta

1

Qeex shuruudaha aqbalida ee saxnaanta, dib u celinta, iyo kharashyada khaladka.

2

Ku tijaabi xogta ku habboon xaaladaha wax soo saarka dhabta ah.

3

Ku dar dib u eegis bini'aadamka si aad u hesho kalsoonida hoose ama saameeynta sare.

4

Lasoco moodeel dhaqaaqa oo dib u cusboonaysii kamarada ama xogta kaydinta ka dib.

Sii wad Sahaminta

Free newsletter

Get the daily AI briefing

Three verified AI stories every weekday morning, written in plain English. Free forever, no ads.

One email each weekday. Unsubscribe in one click. We never sell or share your address.

Test yourself

Take the Residual Networks quiz

Instant feedback on every answer, and a shareable certificate with a verifiable ID once you pass a course.

Bilow kedis

Support free AI education. AI Understanding is a 501(c)(3) nonprofit — no ads, no paywall, ever. Make a donation

Hagaha xiga

Tilmaamaha Shabakadda Ahraamta

Su'aalaha soo noqnoqda

What is Residual Networks?

Shabakadaha Hadhaaga ah (ResNets) waa shabakado neerfaha qoto dheer oo ku dara 'isku-xidhka ka boodka' taasoo u oggolaanaysa lakabyada inay bartaan hagaajin yar halkii ay ka beddeli lahaayeen isbeddel buuxa. Khiyaamadan fudud waxay suurtogal ka dhigtay in la tababaro shabakadaha boqolaal lakab oo qoto dheer, taasoo kicisay boodboodka saxda ah ee aqoonsiga sawirka.

Dhibaato noocee ah ayaa xiriirinta haraaga ah si gaar ah u xalliyeen?

Kahor ResNets, ku darida lakabyo badan ayaa sababtay saxnaanta inay hoos u dhigto xitaa xogta tababarka. Isku dhufashada isku xirka tan ayaa go'an adiga oo ka dhigaya lakabyada si fudud si loo hagaajiyo.

Muxuu block-ga hadhaagu dhab ahaantii u xisaabiyaa sida wax soo saarkiisa?

Soo saarida xannibaadda hadha y = F(x) + x, ku darista hadhaaga la bartay gelinta iyada oo loo marayo isku xidhka boodada.

Waa maxay sababta isku-xirnaanta ka boodi ay u caawiso ardayda qalin-jabinta xilliga tababarka?

Jidka-gaaban ee aqoonsigu wuxuu siinayaa dariiq toos ah gradients si ay gadaal ugu socdaan iyadoo aan isbeddelin, taasoo ka hortagaysa dhibaatada sii liidata ee xirmo qoto dheer.

Qiyaastii immisa lakab ayuu lahaa nooca ResNet ee guuleystay ee 2015?

ResNet-152, oo leh 152 lakab, ayaa ku guuleystay tartanka ImageNet 2015, taasoo muujineysa in shabakadaha aadka u qoto dheer hadda loo tababari karo si guul leh.

Haddii lakabyada baloogga ee haraaga ahi bartaan F(x) = 0, muxuu block-gu sameeyaa?

Marka F(x) = 0, wax soo saarku waa x kaliya, markaa xannibaadda waxay noqotaa khariidad aqoonsi. Tani waxay ka dhigaysaa lakabyo dheeraad ah kuwo aan waxyeello lahayn haddii aan loo baahnayn.