The Study of Sementic Deep Learning Segmentation for Durian Orchard

Abstract

The paper comparatively studies a deep learning based semantic segmentation for segmenting durian orchard environments using MATLAB platform. Experiments consist of four treatments that are the combinations of Deeplabv3+ with base networks including Resnet-18, Resnet-50, Xception and Interceptionresnetv2. IoU metric is utilized as the performance index. The environment is segmented into five classes. The experimental results tested by ANOVA reveal that base networks do not result in a different performance for the class of sky, tree, grass, and road but show different performance for background class.