首页|New Machine Learning Study Findings Recently Were Reported by Researchers at Nat ional Institute of Horticultural Research (Exploration of Convective and Infrare d Drying Effect on Image Texture Parameters of 'Mejhoul' and 'Boufeggous' Date P alm ...)
New Machine Learning Study Findings Recently Were Reported by Researchers at Nat ional Institute of Horticultural Research (Exploration of Convective and Infrare d Drying Effect on Image Texture Parameters of 'Mejhoul' and 'Boufeggous' Date P alm ...)
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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%.”
National Institute of Horticultural Rese archSkierniewicePolandEuropeCyborgsEmerging TechnologiesMachine Lear ning
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