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Title: Intelligent Flower Detection System Using Machine Learning
Authors: Amna Abdulhadi Safar 
Supervisor: Prof. Maytham Hassan Safar
Degree Awarded: M.Sc Computer Engineering
Keywords: Flower Detection;Machine Learning
Issue Date: 2019
Publisher:  Kuwait university - college of graduate studies
Abstract: It is a very hard and a challenging mission to identify different types of flowers as they are very similar. Even expert botanists and gardeners cannot identify some flowers accu- rately. The idea of automating flowers recognition is bewildering as the flowers are not rigid objects and their images can be affected by many external influences. The proposed system use machine learning algorithms to fully automate and increase the accuracy of flower identification. Machine learning model will be used to extract flower’s features automatically, process through different layers of the neural network and finally classify the flower class.
Appears in Programs:0612 Computer Engineering

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