Overview
Nharaunda-Yakavakirwa CNNs (R-CNNs) imhuri yezvinoona zvinhu zvinotanga kurudzira nzvimbo dzevamiriri mumufananidzo, wozoshandisa CNN kurongedza uye kunyatso bhokisi chinhu chimwe nechimwe. Vakashandura chimiro chemufananidzo kuita chizere chekuona chinhu, kutsvaga uye kunyora zvinhu zvakawanda kamwechete.
Nharaunda-Yakavakirwa CNNs ndeyekombuta-yekuona workflows inodudzira kana kuburitsa inooneka midhiya yekuongorora, mashandiro, uye kugadzira.
Deep Dive
Kuiswa kwemifananidzo mhinduro 'chii chiri mumufananidzo uyu?' asi kuonekwa kunofanirawo kupindura kuti 'kupi, uye vangani?' Iyo yekutanga R-CNN (2014) yakashandisa yekunze algorithm (Selective Search) kurumbidza akatenderedza 2,000 matunhu, yakamonyoroka imwe neimwe kusvika kune yakagadziriswa saizi, uye yakamhanyisa CNN pane yega yega, yaive yakarurama asi inorwadza inononoka. Kurumidza R-CNN yakamhanyisa izvi nekumhanyisa CNN kamwe pamusoro pemufananidzo wese uye nekubatanidza maficha padunhu (RoI pooling). Nekukurumidza R-CNN yakabva yatsiva Kutsvaga Kutsvaga neyakadzidziswa Region Proposal Network (RPN), ichiita iyo pombi yese kupera-kusvika-kumagumo uye pedyo-chaiyo-nguva. Mask R-CNN yakawedzera zvakare kuti ibudise pixel-level masks kune chimwe nechimwe chinhu chaonekwa.
Technical Insight
Chinhu chakakosha kusvetuka kusanganisa kweRoI: pane kumhanyisa CNN pabhokisi rega rega rakarongwa, network inounganidza mepu imwe yakagovaniswa yemufananidzo, wozodyara nekugadzirisa maficha ari mukati medunhu rega rega rekufarira kune yakagadziriswa grid. Inokurumidza R-CNN's RPN inotsvedza pamusoro peiyo mepu inofanotaura 'chinhu' zvibodzwa uye mabhokisi ekugadzirisa e preset anchor mabhokisi eakasiyana hukuru uye mareshiyo echikamu, achigadzira zvikumbiro zvinenge zvemahara.
Mastering Dunhu-Yakavakirwa CNNs
Nharaunda-Yakavakirwa CNNs (R-CNNs) imhuri yezvinoona zvinhu zvinotanga kurudzira nzvimbo dzevamiriri mumufananidzo, wozoshandisa CNN kurongedza uye kunyatso bhokisi chinhu chimwe nechimwe. Vakashandura chimiro chemufananidzo kuita chizere chekuona chinhu, kutsvaga uye kunyora zvinhu zvakawanda kamwechete. Nharaunda-Yakavakirwa CNNs ndeyekombuta-yekuona workflows inodudzira kana kuburitsa inooneka midhiya yekuongorora, mashandiro, uye kugadzira. Kuti uvake kunzwisisa kwakadzama, bata Dunhu-Yakavakirwa CNNs semuenzaniso wekushandisa, kwete chinhu chimwe chete: tsanangura zvinodikanwa, kujekesa fungidziro, uye patsanura izvo zvinogona kuitwa nehurongwa hwakavimbika kubva kune zvichiri kuda kutonga kwenyanzvi.
Mukuita, zvikwata zvakasimba zvinoshandisa Dunhu-Yakavakirwa CNNs kuenzanisa nekuita chaiko senge data mhando, kusiyanisa kwemwenje, uye kuenderana kwemazita. Ivo vanonyora zvakajeka maitiro ebudiriro, bvunzo vachipokana ne data rechokwadi uye mafambiro ebasa, uye iterate zvichibva pane zvakacherechedzwa maitiro ekutadza kwete kuhwina-nguva imwe chete yebhenji. Apa ndipo apo kunzwisisa kwe theoretical kunoshanduka kuve kugona kwakasimba pane chigadzirwa, mutemo, uye mashandiro.
Visual AI inogona kuita otomatiki yekuongorora, yekuona, uye yekumaka mabasa pachiyero. Panguva imwecheteyo, kodzero dzeMufananidzo uye kubvumirwa kunogona kuve njodzi dzepamutemo kana hunhu husina kujeka. Nzira yakatsiga ndeyekubatanidza kukurumidza kuyedza nekutonga: mhanyisa vatyairi vendege, tora humbowo, buritsa matanda esarudzo, uye urambe uchivandudza chengetedzo semaitiro emuenzaniso, zvinotarisirwa nemushandisi, uye zvinodikanwa zvekutonga.
Strategic Impact
Visual AI inogona kuita otomatiki yekuongorora, yekuona, uye yekumaka mabasa pachiyero.
Visual AI inogona kuita otomatiki yekuongorora, yekuona, uye yekumaka mabasa pachiyero. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Zvikwata zvekugadzira zvinogona prototype pfungwa nekukurumidza nekudzokororwa kwemaoko mashoma.
Zvikwata zvekugadzira zvinogona prototype pfungwa nekukurumidza nekudzokororwa kwemaoko mashoma. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Mashandisirwo anogona kushandisa masaini emifananidzo nemavhidhiyo ayo aimbove akaoma kugadzirisa.
Mashandisirwo anogona kushandisa masaini emifananidzo nemavhidhiyo ayo aimbove akaoma kugadzirisa. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Real-World Implementation
Kutsvaga uye kuverenga zvigadzirwa pamasherufu ezvitoro zvekutarisira zvinhu
Instance segmentation yemasero kana nhengo mune zvekurapa scans uchishandisa Mask R-CNN
Kuziva hurema uye nzvimbo dzadzo pamutsetse wekugadzira fekitori
Kutsvaga mota dzakawanda uye vanofamba netsoka mune vanozvimirira-kutyaira kamera ma feed
Maitiro Ekuita
Dunhu-Yakavakirwa CNNs mukuita
Kutsvaga uye kuverenga zvigadzirwa pamasherufu ezvitoro zvekutarisira zvinhu.
Kutsvaga uye kuverenga zvigadzirwa pamasherufu ezvitoro zvekutarisira manejimendi Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi ekumucheto, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Dunhu-Yakavakirwa CNNs mukuita
Instance segmentation yemasero kana nhengo mune zvekurapa scans uchishandisa Mask R-CNN.
Instance segmentation yemaseru kana nhengo mune zvekurapa scans vachishandisa Mask R-CNN Matimu anowanzo kuwana mhedzisiro iri nani kana vachitsanangudza zvemhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi ekumucheto, uye kuteedzera zvese zvakawanikwa zvechigadzirwa nemitengo yekukanganisa nekufamba kwenguva.
Dunhu-Yakavakirwa CNNs mukuita
Kuziva hurema uye nzvimbo dzadzo pamutsetse wekugadzira fekitori.
Kuona hurema uye nzvimbo dzadzo pafekitori yekugadzira mutsara Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Dunhu-Yakavakirwa CNNs mukuita
Kutsvaga mota dzakawanda uye vanofamba netsoka mune vanozvimirira-kutyaira kamera ma feed.
Kuwana mota dzakawanda uye vanofamba netsoka mune inozvimirira-inotyaira kamera inodyisa Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi ekumucheto, uye kuteedzera zvese zvakawanikwa zvechigadzirwa nemitengo yekukanganisa nekufamba kwenguva.
Njodzi & Guardrails
Kodzero dzemifananidzo uye kubvumirwa kunogona kuve njodzi dzepamutemo kana provenance isina kujeka.
Kuita kwemuenzaniso kunogona kusiyanisa kupenya, huwandu hwevanhu, uye nharaunda.
Manyepo enhema anogona kusacherechedzwa kunze kwekunge zvikumbaridzo zvekuvimba zvikatariswa.
Implementation Roadmap
Tsanangura maitiro ekugamuchirwa echokwadi, kurangarira, uye mutengo wekukanganisa.
Tsanangura maitiro ekugamuchirwa echokwadi, kurangarira, uye mutengo wekukanganisa. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Edzai nedata rinoenderana nemamiriro chaiwo ekugadzira.
Edzai nedata rinoenderana nemamiriro chaiwo ekugadzira. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Wedzera ongororo yemunhu kune yakaderera-kusavimbika kana yakakwirira-inokanganisa kufanotaura.
Wedzera ongororo yemunhu kune yakaderera-kusavimbika kana yakakwirira-inokanganisa kufanotaura. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Tevera modhi kudonha uye simbisa mushure mekuchinja kwekamera kana dataset.
Tevera modhi kudonha uye simbisa mushure mekuchinja kwekamera kana dataset. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.