Please use this identifier to cite or link to this item:
https://elib.bsu.by/handle/123456789/306264| Title: | Comparative Analysis of Semantic Segmentation Methods for Satellite Images Segmentation |
| Authors: | Bu, Qing Wan, Wei Savitskaya, Elizaveta |
| Keywords: | ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Кибернетика ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Математика |
| Issue Date: | 2023 |
| Publisher: | Minsk : BSU |
| Citation: | Pattern Recognition and Information Processing (PRIP’2023). Artificial Universe: New Horisont : Proceedings of the 16 th International Conference, Belarus, Minsk, October 17–19, 2023 / Belarusian State University : eds. A. Nedzved, A. Belotserkovsky. – Minsk : BSU, 2023. – Pp. 332-337. |
| Abstract: | This paper proposes a comparative analysis of different automatic semantic segmentation methods for satellite images segmentation on the Semantic Drone Dataset with 23 classes (paved-area, dirt, grass, gravel, water, rocks, pool, vegetation, roof, wall, window, door, fence, fence-pole, person, dog, car, bicycle, tree, bald-tree, ar-marker, obstacle, conflicting). We compare such models as U-net, U-net++, FPN, PAN, DeepLabV3, DeepLabV3+ and Transformer architecture model - SegFormer |
| URI: | https://elib.bsu.by/handle/123456789/306264 |
| ISBN: | 978-985-881-522-6 |
| Licence: | info:eu-repo/semantics/openAccess |
| Appears in Collections: | 2023. Pattern Recognition and Information Processing (PRIP’2023). Artificial Intelliverse: Expanding Horizons |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 332-337.pdf | 1,41 MB | Adobe PDF | View/Open |
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