首页|Investigators from University of Toronto Report New Data on Machine Learning (Ad vances In Machine Learning and Deep Learning Applications Towards Wafer Map Defe ct Recognition and Classification: a Review)
Investigators from University of Toronto Report New Data on Machine Learning (Ad vances In Machine Learning and Deep Learning Applications Towards Wafer Map Defe ct Recognition and Classification: a Review)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators publish new report on Ma chine Learning. According to news reportingout of Toronto, Canada, by NewsRx ed itors, research stated, “With the high demand and sub-nanometerdesign for integ rated circuits, surface defect complexity and frequency for semiconductor wafers haveincreased; subsequently emphasizing the need for highly accurate fault det ection and root-cause analysissystems as manual defect diagnosis is more time-i ntensive, and expensive. As such, machine learningand deep learning methods hav e been integrated to automated inspection systems for wafer map defectrecogniti on and classification to enhance performance, overall yield, and cost-efficiency .”
TorontoCanadaNorth and Central Ameri caCyborgsEmerging TechnologiesMachine LearningUniversity of Toronto
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