An adaptive multichannel DeepLabv3 + for semantic segmentation of aerial images using improved Beluga Whale Optimization Algorithm
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-17247-z.pdf
Reference43 articles.
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2. Esmael Agnaldo Aparecido, Santos Jefersson Alex Dos, da Silva Ricardo, Torres, (2018) On the ensemble of multiscale object-based classifiers for aerial images: a comparative study. Multimedia Tools Appl 77:24565–24592
3. Khan SD, Alarabi L, Basalamah S (2023) Segmentation of farmlands in aerial images by deep learning framework with feature fusion and context aggregation modules. Multimed Tools Appl 1–20. https://doi.org/10.1007/s11042-023-14962-5
4. Liu C, Wu Y, Liu J, Sun Z (2021) Improved YOLOv3 network for insulator detection in aerial images with diverse background interference. Electronics 10(7):771
5. Hong Z et al (2022) Highway crack segmentation from unmanned aerial vehicle images using deep learning. IEEE Geosci Remote Sens Lett 19:1–5
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