A leaf recognition algorithm for plant classification using probabilistic neural network
2007 IEEE international symposium on signal processing and …, 2007•ieeexplore.ieee.org
In this paper, we employ probabilistic neural network (PNN) with image and data processing
techniques to implement a general purpose automated leaf recognition for plant
classification. 12 leaf features are extracted and orthogonalized into 5 principal variables
which consist the input vector of the PNN. The PNN is trained by 1800 leaves to classify 32
kinds of plants with an accuracy greater than 90%. Compared with other approaches, our
algorithm is an accurate artificial intelligence approach which is fast in execution and easy in …
techniques to implement a general purpose automated leaf recognition for plant
classification. 12 leaf features are extracted and orthogonalized into 5 principal variables
which consist the input vector of the PNN. The PNN is trained by 1800 leaves to classify 32
kinds of plants with an accuracy greater than 90%. Compared with other approaches, our
algorithm is an accurate artificial intelligence approach which is fast in execution and easy in …
In this paper, we employ probabilistic neural network (PNN) with image and data processing techniques to implement a general purpose automated leaf recognition for plant classification. 12 leaf features are extracted and orthogonalized into 5 principal variables which consist the input vector of the PNN. The PNN is trained by 1800 leaves to classify 32 kinds of plants with an accuracy greater than 90%. Compared with other approaches, our algorithm is an accurate artificial intelligence approach which is fast in execution and easy in implementation.
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