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- W3047367639 abstract "Plants are the primary food source of humans. They are the raw material of most medicines. Therefore, it was necessary to use artificial intelligence to help those interested in plants to classify and identify various plants types quickly and accurately. In this article we present Neural Shifted Legendre-Fourier Moments, we used shifted Legendre-Fourier moments to extract features from leaves images and build descriptor vectors. These vectors are the inputs of the artificial neural network. We tested this model on MalayaKew (MK) Leaf dataset and we got important results. The validity of this proposed method has been provided under different transformations." @default.
- W3047367639 created "2020-08-10" @default.
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- W3047367639 date "2020-01-01" @default.
- W3047367639 modified "2023-10-17" @default.
- W3047367639 title "Plants Classification Using Neural Shifted Legendre-Fourier Moments" @default.
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- W3047367639 doi "https://doi.org/10.1007/978-3-030-53187-4_18" @default.
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