@inproceedings{c222a204a50246f7acb88163c3c64c0d,
title = "Lightweight UAV Image Segmentation Model Design with Edge Feature Aggregation",
abstract = "Nowadays, Unmanned Aerial Vehicles (UAVs) tend to become an attractable platform for smart city applications, especially for environmental sensing tasks. UAV downwards view image segmentation can extract meaningful information, but the challenge lies in segmenting small-size objects. This paper proposed a reasonable method where edge features were aggregated to enhance the performance of segmentation results, together with a suitable re-weighting method to alleviate the imbalance of interested object class distribution. The effectiveness of the designed network architecture was proven by experimental results that around a 2-4\% increase of IoU for aimed small-size classes was achieved. Additionally, the proposed model remains in a lightweight structure.",
keywords = "Edge feature, Imbalanced classes, Lightweight model, Semantic segmentation, UAV image",
author = "Fengyufan Yang and Liye Jia and Erick Purwanto and Jeremy Smith and Man, \{Ka Lok\} and Yutao Yue",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 9th International Conference on Platform Technology and Service, PlatCon 2023 ; Conference date: 16-08-2023 Through 18-08-2023",
year = "2023",
doi = "10.1109/PlatCon60102.2023.10255196",
language = "English",
series = "2023 International Conference on Platform Technology and Service, PlatCon 2023 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "7--12",
booktitle = "2023 International Conference on Platform Technology and Service",
}