摘要
由一名新闻记者-机器人与机器学习每日新闻的工作人员新闻编辑-调查人员发布了关于人工智能的新报告。根据NewsRx Journali STS在克罗地亚萨格勒布的新闻报道，研究表明，“本文提出了一项研究，重点是通过数字图像分析开发覆盖系数和孔隙度计算的稳健算法。”这项研究的资助者包括克罗地亚科学基金会；扎格雷布大学。新闻记者引用了扎格雷大学纺织技术学院的一篇研究文章：“基于机器学习的基于织物参数的有效覆盖因子预测计算模型也已经开发出来。在MATLAB中设计并实现了五种算法：单T Hreshold算法(ST)；多线性阈值算法ml-1和ml-2；以及通过Otzu方法获得的多阈值D算法，mt-1和mt-2.这些算法应用于足球、游泳和休闲用针织面料。ml-1和mt-1采用多阈值算法优于单一阈值算法。ml-1变体的平均孔隙率最高,为95.24%。对比分析表明,Varia NTS ML-2和MT-2的覆盖因子比ML-1和MT-1低,但能以较高的可靠性检测织物的潜在空隙面积。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Investigators publish new report on artificial in telligence. According to news reporting from Zagreb, Croatia, by NewsRx journali sts, research stated, “This paper presents a study focused on developing robust algorithms for cover factor and porosity calculation through digital image analy sis.” Funders for this research include Croatian Science Foundation; University of Zag reb. The news journalists obtained a quote from the research from University of Zagre b Faculty of Textile Technology: “Computational models based on machine learning for efficient cover factor prediction based on fabric parameters have also been developed. Five algorithms were devised and implemented in MATLAB: the single t hreshold algorithm (ST); multiple linear threshold algorithms, ML-1 and ML-2; an d algorithms with multiple thresholds obtained by the Otzu method, MT-1 and MT-2 . These algorithms were applied to knitted fabrics used for football, swimming, and leisure. Algorithms ML-1 and MT-1, employing multiple thresholds, outperform ed the single threshold algorithm. The ML-1 variant yielded the highest average porosity value at 95.24%, indicating the importance of adaptable th resholding in image analysis. Comparative analysis revealed that algorithm varia nts ML-2 and MT-2 obtain lower cover factors compared to ML-1 and MT-1 but can d etect potential void areas in fabrics with higher reliability.”
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