Research from Guru Ghasidas Vishwavidyalaya in the Area of Support Vector Machin es Described (Maximizing steel slice defect detection: Integrating ResNet101 dee p features with SVM via Bayesian optimization)
Guru Ghasidas Vishwavidyalaya在所述支持向量机领域的研究(最大化钢片缺陷检测：通过贝叶斯优化将ResNet101 dee p特征与SVM集成)
Research from Guru Ghasidas Vishwavidyalaya in the Area of Support Vector Machin es Described (Maximizing steel slice defect detection: Integrating ResNet101 dee p features with SVM via Bayesian optimization)
Guru Ghasidas Vishwavidyalaya在所述支持向量机领域的研究(最大化钢片缺陷检测：通过贝叶斯优化将ResNet101 dee p特征与SVM集成)
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摘要
由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-调查人员讨论支持向量机的新发现。根据新闻报道根据NewsRx编辑的Guru Ghasidas Vi Shwavidyalaya，研究表明，“准确的检测”钢表面缺陷的去除对保持钢产品质量标准至关重要。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators discuss new findings in support vector machines. According to news reportingout of the Guru Ghasidas Vi shwavidyalaya by NewsRx editors, research stated, “Accurate detectionof defects on steel surfaces is crucial for maintaining quality standards in steel product ion.”
Key words
Guru Ghasidas Vishwavidyalaya/Machine L earning/Support Vector Machines
NETL
NSTL