Local linear mapping neural networks for pattern recognition of plants

摘要

A new neural network architecture for classification purposes is proposed. The Self-Organizing Map (SOM) Neural Network is used in a supervised way for a classification task. The neurons of the SOM become associated with Local Linear Mappings. Error information obtained during training is used in novel learning algorithm to train the classifier. The proposed method achieves fast convergence and good generalisation. The classification method is then applied in a precision farming application, the classification of crops and weeds using spectral properties. The classification performance of the proposed method is proven superior compared to other statistical and neural classifiers.