Research on semantic segmentation of UAV images based on deep learning

Lihua He; Xinyan Cao; Yuheng Wang; Liye Ren

doi:10.1117/12.2641404

4 August 2022 Research on semantic segmentation of UAV images based on deep learning

Lihua He, Xinyan Cao, Yuheng Wang, Liye Ren

Proceedings Volume 12306, Second International Conference on Digital Signal and Computer Communications (DSCC 2022); 123060T (2022) https://doi.org/10.1117/12.2641404
Event: Second International Conference on Digital Signal and Computer Communications (DSCC 2022), 2022, Changchun, China

Abstract

UAV technology has developed rapidly in recent years, Images extracted by UAV are widely used in urban division, crop classification, land monitoring etc. However, there are problems in UAV image segmentation such as image category imbalance, object scale variation, and insufficient utilization of contextual information, etc. To address the above problems, this paper uses optimized deeplabv3+ network model, and cross-entropy loss function for balancing the dataset samples in the experimental process for image semantic segmentation research. The results show that the algorithm of this paper has a high accuracy rate for semantic segmentation of UAV images, and can recognize each category of UAV images better, and the segmentation effect is better.

Citation Download Citation

Lihua He, Xinyan Cao, Yuheng Wang, and Liye Ren "Research on semantic segmentation of UAV images based on deep learning", Proc. SPIE 12306, Second International Conference on Digital Signal and Computer Communications (DSCC 2022), 123060T (4 August 2022); https://doi.org/10.1117/12.2641404

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KEYWORDS

Image segmentation

Unmanned aerial vehicles

Convolution

Image processing algorithms and systems

Feature extraction

Image processing

Image classification

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