Plant Phenomics / 2020 / Article / Fig 1

Research Article

Generalized Linear Model with Elastic Net Regularization and Convolutional Neural Network for Evaluating Aphanomyces Root Rot Severity in Lentil

Figure 1

Data analysis approaches: training and optimization. (a) Imagery datasets, (b) distribution of ARR visual disease scores and ARR disease classes within experiments, (c) distribution of ARR visual disease scores and ARR disease classes within root_1 dataset () and root_2 dataset (), (d) CNN architecture, and (e) generalized mixed model with EN regularization optimization and feature selection. Conv: convolutional layer; BN: batch normalization layer; Relu: rectified linear unit layer; Pool: max pooling layer; Dropout: dropout layer; fc: fully connected layer; softmax: softmax layer; cv: cross-validation.
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