首页|Reports from University of Auckland Describe Recent Advances in Machine Learning (Integrating Image Analysis and Machine Learning for Moisture Prediction and Ap pearance Quality Evaluation: A Case Study of Kiwifruit Drying Pretreatment)
Reports from University of Auckland Describe Recent Advances in Machine Learning (Integrating Image Analysis and Machine Learning for Moisture Prediction and Ap pearance Quality Evaluation: A Case Study of Kiwifruit Drying Pretreatment)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on artificial intell igence are discussed in a new report. According to news originating from Aucklan d, New Zealand, by NewsRx editors, the research stated, "The appearance of dried fruit clearly influences the consumer's perception of the quality of the produc t but is a subtle and nuanced characteristic that is difficult to quantitatively measure, especially online." The news editors obtained a quote from the research from University of Auckland: "This paper describes a method that combines several simple strategies to asses s a suitable surrogate for the elusive quality using imaging, combined with mult ivariate statistics and machine learning. With such a convenient tool, this stud y also shows how one can vary the pretreatments and drying conditions to optimiz e the resultant product quality. Specifically, an image batch processing method was developed to extract color (hue, saturation, and value) and morphological (a rea, perimeter, and compactness) features. The accuracy of this method was verif ied using data from a case study experiment on the pretreatment of hot-air-dried kiwifruit slices. Based on the extracted image features, partial least squares and random forest models were developed to satisfactorily predict the moisture r atio (MR) during drying process. The MR of kiwifruit slices during drying could be accurately predicted from changes in appearance without using any weighing de vice."
University of AucklandAucklandNew Ze alandAustralia and New ZealandCyborgsEmerging TechnologiesMachine Learni ng
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