Qeexid
CNN-yadu waxay isticmaalaan layers convolutional ah oo wadaagaya filter-yo goboladda booska oo dhan, waxayna si hufan u qabsadaan cirifyo, tayooyin (textures), iyo walxaha. Pooling layers waxay hoos u dhigtaa cabbirka; layers si buuxda isku xiran badanaa ayaa dhammaystiraya kala-soocidda.
Waxay xukumeen computer vision ka hor inta vision transformers ay tartan la noqoneen.
Si fudud
CNN waa sida in sawir lagu baadho weel-shaash yaryar oo mid kasta raadinaya qaab gaar ah — xariiqyo, geesaha, indhaha — kadibna la isku daro ogaanshahaas.
Halka aad ka aragto
- Kala-soocidda sawirrada iyo ogaanshaha walxaha.
- Falanqaynta rayga-gacanta caafimaadka (X-ray) iyo MRI-ga.
- Moodeelada spectrogram-ka codka ee hawlaha hadalka.
Sida ay u shaqeyso
1.Convolve
Filter-yadu waxay ku socdaan wax-soo-galinta iyagoo soo saaraya feature map-yo.
2.Firaysii oo pool
Aan-toosnaan iyo hoos-u-dhigid isku darsan.
3.Isku kaydso layers
Layers-ka qoto-dheer waxay arkaan booska aqbalka (receptive field) oo weyn.
4.Kala-sooc ama ogow
Head-ku wuxuu soo saaraa summado ama sanduuqyo xadka (bounding boxes).
Maxay muhiim u tahay
- CNN-yadu weli waxay hufsan yihiin oo xoog leeyihiin hawlo badan oo vision iyo signal ah.
Inta badan la khaldo
CNN-yadu waa la duugoobay sababtoo ah transformers.
Transformers ayaa hormariya benchmark-yo badan, laakiin CNN-yadu weli si ballaaran ayaa loo isticmaalaa xagga xawaaraha, cabbirka, iyo inductive bias-ka.