The invasion of the tomato leaf miner (Tuta absoluta) poses a significant threat to tomato
productivity, leading to substantial yield losses for farmers. Currently, there is a lack of
reliable methods for quantifying the effects of Tuta absoluta at an early stage before it
causes significant damage. This research proposes a deep Convolutional Neural Network
(CNN) model for the segmentation-based quantification of Tuta absoluta on tomato plants.
The proposed quantification method employed a Mask RCNN model that achieved a mAP of …