Data Augmentation for Improving SSD Performance in Rainy Weather Conditions
Quoc-Viet Hoang, Trung-Hieu Le, Shih-Chia Huang · 2020
This paper focuses on using data augmentation to improve the performance of Single Shot Multibox Detector (SSD) in rainy weather conditions. Data augmentation is applied by generating synthetic rain on a set of clear images to expand the dataset for training. The experimental results show that the performance of SSD model improves by up to 16.82% when being trained on the proposed augmented synthetic dataset.