
Aprendizagem por computador com base na visão na aciaria: Tecnologia de aprendizagem de máquinas baseada em visão por computador para melhorar a produção na aciaria
توسط
Gedela Praveen
هنوز رتبهبندی نشده است
Science & Technology
فرمت
جلد نرم
صفحات
68
زبان
پرتغالی
منتشر شده
May 26, 2022
ناشر
Edições Nosso Conhecimento
ISBN-10
6204800817
ISBN-13
9786204800813
توضیحات
The work delves into the transformative potential of Computer Vision Machine Learning (CVML) within the steelmaking industry. By exploring the intersection of advanced machine learning techniques and visual processing, the authors highlight how these innovations can significantly enhance production efficiency and quality in steel manufacturing processes.
Gedela Praveen and Sanjay V. Gurme meticulously examine various case studies and applications of CVML, providing real-world examples of its successful implementation. Their analysis focuses on how visual data can be harnessed to optimize operations, reduce waste, and improve decision-making in high-stakes production environments.
As industries increasingly seek smarter solutions, this exploration offers valuable insights into integrating cutting-edge technology into traditional manufacturing settings. With a clear focus on practical applications, the authors aim to bridge the gap between theoretical advancements and their real-world implications.
Ultimately, this comprehensive examination serves as a critical resource for professionals and researchers in engineering, manufacturing, and technology, urging them to embrace innovative approaches for a more efficient and sustainable future in steel production.
Gedela Praveen and Sanjay V. Gurme meticulously examine various case studies and applications of CVML, providing real-world examples of its successful implementation. Their analysis focuses on how visual data can be harnessed to optimize operations, reduce waste, and improve decision-making in high-stakes production environments.
As industries increasingly seek smarter solutions, this exploration offers valuable insights into integrating cutting-edge technology into traditional manufacturing settings. With a clear focus on practical applications, the authors aim to bridge the gap between theoretical advancements and their real-world implications.
Ultimately, this comprehensive examination serves as a critical resource for professionals and researchers in engineering, manufacturing, and technology, urging them to embrace innovative approaches for a more efficient and sustainable future in steel production.
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