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Understand These 5 Key Deep Learning Classification Metrics for Better Application Success

Product quality is the lifeblood of most companies. Getting it right time and again leads to customer trust, positive word of mouth, fewer costly recalls, and ultimately better business outcomes. In a factory or production line, relying on machine vision systems throughout every step of production is one of the best investments to deliver quality products. Specifically, deep learning tools such as a classifier, help manufacturers identify potential quality control issues on the production line to limit overall flaws in finished products.

The classifier is an important inspection tool because it is not just enough for the production line to identify defects or damaged parts and pull them out of production. Those defects must also be classified so the inspection system can identify patterns to determine whether one defect is a scratch, or another is a dent, for example. Correct classifications of these production flaws keep bad products off the market, while wrong predictions keep good products off the shelves, bogging down production and adding to costs.

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