{"id":462,"date":"2020-12-28T21:11:06","date_gmt":"2020-12-28T21:11:06","guid":{"rendered":"http:\/\/svetlezitrky.tech\/?page_id=462"},"modified":"2023-07-15T11:49:22","modified_gmt":"2023-07-15T11:49:22","slug":"neuronove-site","status":"publish","type":"page","link":"https:\/\/visimatic.cz\/en\/neuronove-site\/","title":{"rendered":"Neural networks and Deep learning"},"content":{"rendered":"
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Neural networks and Deep learning<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Machine vision combined with neural networks<\/strong> and artificial intelligence<\/strong> can solve previously unsolvable problems.\u00a0 Our neural network-enhanced vision systems for the most demanding applications think like a human in principle, but evaluate product quality with the extreme speed, accuracy and relentlessness of a machine. <\/p>\n

The control system for evaluating the quality of a given product is trained in a similar way to training a new employee. The machine vision system learns what is considered a defect or defect in the product, what colors or shapes this defect may have based on the product samples that are presented, which are both high and low quality, and then can reliably detect these defects in various places in the product. For each product, the system evaluates the size, location and type of defect. Then, based on the tolerances you specify, a decision will be made as to whether the product is of good or poor quality.<\/p>\n

Neural networks are most commonly used for:<\/b><\/p>\n

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  •  detection of unpredictable surface defects<\/b> - corrosion, scratches, chips and various defects in metals, glass, wood and other materials<\/li>\n
  •  differentiation of almost identical parts or shapes<\/b> and checking the correct orientation of easily interchangeable parts.<\/li>\n
  • checking for any deviation from the correct condition of the parts<\/b> - the system learns the appearance of the correct product and automatically detects even minor deviations from the sample piece.<\/li>\n<\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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    Detection of surface defects in wood<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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    Neural networks and artificial intelligence are absolutely perfect tools for checking the quality of the wood surface, where you can check, for example, the presence of knots, staining, chipping or any other defects.<\/p>

    Na obr\u00e1zku n\u00ed\u017ee m\u016f\u017eete vid\u011bt uk\u00e1zku lokalizace suk\u016f a jin\u00fdch tmav\u00fdch m\u00edst na d\u0159ev\u011bn\u00fdch prknech. V n\u00e1sleduj\u00edc\u00edch kroc\u00edch kontroly kvality by do\u0161lo k vyhodnocen\u00ed polohy a velikosti vad a na z\u00e1klad\u011b t\u011bchto parametr\u016f k rozt\u0159\u00edd\u011bn\u00ed do t\u0159\u00edd kvality dle v\u00e1mi nastaven\u00fdch toleranc\u00ed.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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    \r\n\t\t\tBefore<\/span>\r\n\t\t\tAfter<\/span>\r\n\"Suky\"Detekce\t\t<\/div>\r\n\t\t