نوع مقاله : مقاله مروری
نویسندگان
1 دانشیار گروه مهندسی مکانیک بیوسیستم، پردیس ابوریحان، دانشگاه تهران
2 گروه فنی کشاورزی-پردیس ابوریحان- دانشگاه تهران تهران-ایران
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Demand for quality products has been increasing for decades and is now increasing. Quality control ensures increased product production using an automated, cost-effective and non-destructive method. In the last few years, significant results have been achieved in various agricultural and food sectors. These achievements are integrated with machine learning techniques in a landscape approach that contrasts with color, texture, shape, spectral analysis of the image of objects. Despite having different programs and many different machine learning techniques, this study only explains the statistical technologies of machine learning with machine vision systems in agriculture due to the wide range of machine learning programs. Two types of machine learning techniques, such as supervised and unsupervised learning, have been used for agriculture. In this research, software solutions rely on image processing techniques such as: artificial neural networks, genetic algorithm, deep learning and fuzzy logic for automatic detection as well as classification of different degrees of fruit. There is also more reference to the study and description of product classification methods that using the mentioned algorithms and their relationship with the software can be a big step in quality classification of products.
کلیدواژهها [English]
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