Fig. 4From: HairNet: a deep learning model to score leaf hairiness, a key phenotype for cotton fibre yield, value and insect resistanceNetwork architecture of the proposed deep learning model to score cotton leaf hairiness. The proposed model consists of four main parts. First the image is passed through a Data Augmentation module (a) that augments the image by applying a variety of image processing techniques. Processed images are then passed to a Feature Extraction Network (b) that extracts discriminative visual features from the image representation. Extracted visual features are then passed to a simple Classification Neural Network (c) that assigns each input image to a specific score. Raw scores are then processed by the Leaf Hairiness Scoring module (d) which generates three accuracy metrics for scoring cotton leaf hairinessBack to article page