Overview
Optical Character Recognition (OCR) inoshandura mifananidzo yezvinyorwa - zvinyorwa zvakaongororwa, mafoto ezviratidzo, maPDF - kuita zvinyorwa zvinoverengeka nemuchina. Ndiro bhiriji rinoita kuti nyika yakadhindwa uye yakanyorwa nemaoko iwanikwe uye ikwanise kushandisika.
Optical Character Recognition ndeyekombuta-yekuona workflows inodudzira kana kugadzira midhiya yekuona yekuongorora, mashandiro, uye kugadzira.
Deep Dive
OCR inoshandura mapixels anoita semavara kuita macode chaiwo anogona kuchengetwa nekombuta nekugadzirisa. Classic OCR yakashanda mumatanho: chenesa uye de-skew mufananidzo, tsvaga zvinyorwa zvinyorwa, zvigovane mumitsara uye yega glyphs, wozoisa glyph yega yega nekufananidza chimiro chayo nemaitiro anozivikanwa. Yemazuvano OCR yakanyanya neural: convolutional network inoverenga zvinoonekwa, uye inoteedzana modhi (kazhinji ine CTC kurasikirwa kana yekutarisisa-based decoder) inofanotaura tambo dzese pasina kuda akakwana hunhu segmentation. Izvi zvinobata mavara ekutuka, anopindirana, uye mafonti akasiyana zviri nani. Injini dzakaita seTesseract, plus Cloud services kubva kuGoogle, Amazon, uye Microsoft, zvino dzasvika pakurongeka kwepamusoro pakudhindwa kwakachena uye kubata mitauro yakawanda nezvinyorwa.
Technical Insight
Kubudirira kukuru kwaive Connectionist Temporal Classification (CTC). Masisitimu echikuru aifanira kucheka izwi kuita mavara akapatsanurwa asati avaziva - kukanganisa-kukanganisa kana mavara achinge abata kana smear. CTC inobvumira inodzokororwa kana yetransformer network kuburitsa mukana kune yega yega chimedu chega chega chemufananidzo, yobva yadonha inodzokororwa uye isina kuvhara kuburitsa izwi rekupedzisira. Izvi zvinobvisa brittle segmentation nhanho uye inoita kuti modhi idzidze kurongeka pakati pemapikisesi nemabhii otomatiki kubva kune akanyorwa mufananidzo-mavara maviri.
Mastering Optical Character Recognition
Optical Character Recognition (OCR) inoshandura mifananidzo yezvinyorwa - zvinyorwa zvakaongororwa, mafoto ezviratidzo, maPDF - kuita zvinyorwa zvinoverengeka nemuchina. Ndiro bhiriji rinoita kuti nyika yakadhindwa uye yakanyorwa nemaoko iwanikwe uye ikwanise kushandisika. Optical Character Recognition ndeyekombuta-yekuona workflows inodudzira kana kugadzira midhiya yekuona yekuongorora, mashandiro, uye kugadzira. Kuti uvake kunzwisisa kwakadzama, bata Optical Character Recognition semuenzaniso wekushandisa, kwete chinhu chimwe chete: tsanangura zvinodiwa, kujekesa fungidziro, uye patsanura izvo zvinogona kuitwa nehurongwa hwakavimbika kubva kune zvichiri kuda kutonga kwenyanzvi.
Mukuita, zvikwata zvakasimba zvinoshandisa Optical Character Recognition chiyero chechokwadi nemashandiro anoita semhando yedata, kusiyana 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
Nharembozha dzekubhengi maapplication anoverenga account yecheki yepepa, nzira, uye minda yehuwandu kuitira kuti vashandisi vakwanise kuisa nemufananidzo
Google Lens uye Apple Live Text inoita kuti ukope mavara kubva pamufananidzo kana kushandura menyu yekunze munguva chaiyo.
Kuita dhijitari bepanhau renhoroondo uye raibhurari zvinyorwa kuitira kuti zvinyorwa zvizere zvive keyword-kutsvaga
Otomatiki invoice uye risiti kugadzirisa mune accounting software iyo inobvisa mutengesi, zuva, uye zviyero.
Maitiro Ekuita
Optical Character Recognition mukuita
Nharembozha dzebhengi maapplication anoverenga account yecheki yepepa, nzira, uye minda yehuwandu kuitira kuti vashandisi vagone kuisa nemufananidzo.
Nharembozha dzebhengi dzemabhengi dzinoverenga account yecheki yebepa, nzira, uye minda yehuwandu kuitira kuti vashandisi vakwanise kuisa nemifananidzo Matimu anowanzo kuwana mibairo iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Optical Character Recognition mukuita
Google Lens uye Apple Live Text inoita kuti ukope mavara kubva pamufananidzo kana kushandura menyu yekunze munguva chaiyo.
Google Lens uye Apple Live Text inokutendera kuti ukope mavara kubva pamufananidzo kana kushandura menyu yekunze munguva chaiyo Matimu anowanzo kuwana mibairo iri nani kana achinge atsanangura mhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Optical Character Recognition mukuita
Kuita dhijitari bepanhau renhoroondo uye raibhurari zvinyorwa kuitira kuti zvinyorwa zvizere zvive keyword-kutsvaga.
Kuisa dhijitari bepanhau renhoroondo uye raibhurari dura kuitira kuti iwo azere mameseji ave keyword-anotsvakwa Matimu anowanzo kuwana zvirinani zvibodzwa kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi ekumucheto, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Optical Character Recognition mukuita
Otomatiki invoice uye risiti kugadzirisa mune accounting software inobvisa mutengesi, zuva, uye huwandu.
Otomatiki invoice uye risiti kugadzirisa mune accounting software iyo inobvisa mutengesi, zuva, uye mahota 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.
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.