| Περίληψη: | With the development of technology and automation in production processes comes man's need for further learning and research. This thesis focuses on the field of image analysis and pattern recognition. After an extensive theoretical analysis starting from the classical classification theory with reference also to the simple perceptron, which is a foundation stone for classifiers, passing through the texture analysis to extract and use it as a feature and the theory of mixtures of distributions and the EM (Expectation-Maximization) Algorithm, it concludes with a practical application. This is in the field of agriculture and the rapid development of the use of artificial intelligence (AI) in it and relates to disease identification in strawberries using machine learning techniques. For this reason there is a discussion of various strawberry diseases after the introduction of the topic. At the end, the experimental procedure and data are presented, and the thesis concludes with the findings and suggestions for future research.
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