[{"data":1,"prerenderedAt":136},["ShallowReactive",2],{"glossary-en-computer-vision":3},{"id":4,"title":5,"body":6,"description":123,"extension":124,"meta":125,"navigation":131,"path":132,"seo":133,"stem":134,"__hash__":135},"en_glossary\u002Fen\u002Fglossary\u002Fcomputer-vision.md","What is Computer Vision?",{"type":7,"value":8,"toc":113},"minimark",[9,13,27,32,65,69,95,99,106],[10,11,5],"h2",{"id":12},"what-is-computer-vision",[14,15,16,20,21,26],"p",{},[17,18,19],"strong",{},"Computer vision"," is the branch of AI that extracts meaningful information from camera, drone or satellite images. Today it is mostly done with ",[22,23,25],"a",{"href":24},"\u002Fen\u002Fglossary\u002Fdeep-learning","deep learning"," models.",[28,29,31],"h3",{"id":30},"core-tasks","Core Tasks",[33,34,35,42,48,59],"ul",{},[36,37,38,41],"li",{},[17,39,40],{},"Classification",": what is the whole image? (\"defective\", \"OK\")",[36,43,44,47],{},[17,45,46],{},"Object detection",": where are the objects, and how many?",[36,49,50,53,54,58],{},[17,51,52],{},"Segmentation",": the outline of each object or each pixel. See ",[22,55,57],{"href":56},"\u002Fen\u002Fglossary\u002Finstance-segmentation","Instance Segmentation",".",[36,60,61,64],{},[17,62,63],{},"Vectorisation",": turning pixel masks into lines and polygons, e.g. CAD drawings from orthophotos.",[28,66,68],{"id":67},"industrial-use","Industrial Use",[33,70,71,77,83,89],{},[36,72,73,76],{},[17,74,75],{},"Agriculture",": tree counting and health tracking in drone imagery.",[36,78,79,82],{},[17,80,81],{},"Mapping",": automatic drawing of buildings, roads and boundaries from orthophotos.",[36,84,85,88],{},[17,86,87],{},"Manufacturing",": surface defects, missing parts and label checks on the line.",[36,90,91,94],{},[17,92,93],{},"Safety",": detecting helmets, vests and danger-zone intrusions.",[28,96,98],{"id":97},"challenges-in-the-field","Challenges in the Field",[14,100,101,102,58],{},"A model that scores well in the lab can drop under different lighting, a different camera or a different region. That is why testing must happen under conditions not seen in training. See ",[22,103,105],{"href":104},"\u002Fen\u002Fglossary\u002Foverfitting","Overfitting",[14,107,108,109],{},"Our services: ",[22,110,112],{"href":111},"\u002Fen\u002Fsolutions\u002Findustrial-ai","Industrial AI",{"title":114,"searchDepth":115,"depth":115,"links":116},"",2,[117],{"id":12,"depth":115,"text":5,"children":118},[119,121,122],{"id":30,"depth":120,"text":31},3,{"id":67,"depth":120,"text":68},{"id":97,"depth":120,"text":98},"The branch of AI that extracts meaning from images: classification, detection, segmentation and industrial use cases.","md",{"tags":126,"translation":130},[127,128,129,52,112],"Computer Vision","Deep Learning","Drone","bilgisayarli-goru",true,"\u002Fen\u002Fglossary\u002Fcomputer-vision",{"title":5,"description":123},"en\u002Fglossary\u002Fcomputer-vision","olBAd_1mQOh0THxNmjPDhZ2HiAkzsde7zinzH7atiOk",1793875325186]