摘要
由机器人与机器学习每日新闻的新闻记者兼新闻编辑-研究人员详细介绍了人工智能的新数据。据Ne wsRx记者从波兰斯基尔涅维斯发回的消息称，研究表明，“枣树(*凤凰指形植物*L .)”属于‘Mejhoul’和‘Boufegous’品种的果实样品在添马舰时期被harved并用于我们的实验。这项研究的财政支持者包括国家科学中心和欧洲联盟在玛丽·斯克尔·奥多斯卡-居里下的地平线2020研究和创新计划。新闻编辑引用了美国国家葡萄栽培研究所的一句话：“扫描前，用60°C对流干燥和60°C红外干燥，频率为50Hz进行扫描，并对200个新鲜、对流干燥的枣仁进行扫描试验。”采用RGB、Lab、XYZ和UVS C三种颜色模型,提取枣果实图像纹理参数,根据所选图像纹理,采用Bayes、Trees、Lazy、Functions等分类算法,建立枣果实新鲜和干燥样品的分类模型。对‘梅胡尔’和‘博乌弗古斯’品种，利用随机森林建立的模型都是准确和成功的，新鲜、对流干燥和红外干燥‘梅胡尔’品种的平均分类精度达到99.33%，而新鲜、对流干燥和红外干燥‘博弗古斯’品种的平均分类精度为94.33%。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in artific ial intelligence. According to news originating from Skierniewice, Poland, by Ne wsRx correspondents, research stated, “Date palm (* * Phoenix dactylifera* * L.) fruit samples belonging to the ‘Mejhoul’ and ‘Boufeggous’ cultivars were harves ted at the Tamar stage and used in our experiments.” Financial supporters for this research include National Science Centre And The E uropean Union’s Horizon 2020 Research And Innovation Program Under The Marie Skl odowska-curie. The news editors obtained a quote from the research from National Institute of H orticultural Research: “Before scanning, date samples were dried using convectiv e drying at 60 °C and infrared drying at 60 °C with a frequency of 50 Hz, and th en they were scanned. The scanning trials were performed for two hundred date pa lm fruit in fresh, convective-dried, and infrared-dried forms of each cultivar u sing a flatbed scanner. The image-texture parameters of date fruit were extracte d from images converted to individual color channels in RGB, Lab, XYZ, and UVS c olor models. The models to classify fresh and dried samples were developed based on selected image textures using machine learning algorithms belonging to the g roups of Bayes, Trees, Lazy, Functions, and Meta. For both the ‘Mejhoul’ and ‘Bo ufeggous’ cultivars, models built using Random Forest from the group of Trees tu rned out to be accurate and successful. The average classification accuracy for fresh, convective-dried, and infrared-dried ‘Mejhoul’ reached 99.33% , whereas fresh, convective-dried, and infrared-dried samples of ‘Boufeggous’ we re distinguished with an average accuracy of 94.33%.”
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