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An Intelligent Remote Sensing Image Quality Inspection System

arXiv 2307.11965 ↗First posted 22 Jul 2023cs.CVcited by 0

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Abstract (arXiv)

Due to the inevitable presence of quality problems, quality inspection of remote sensing images is indeed an indispensable step between the acquisition and the application of them. However, traditional manual inspection suffers from low efficiency. Hence, we propose a novel deep learning-based two-step intelligent system consisting of multiple advanced computer vision models, which first performs image classification by SwinV2 and then accordingly adopts the most appropriate method, such as semantic segmentation by Segformer, to localize the quality problems. Results demonstrate that the proposed method exhibits excellent performance and efficiency, surpassing traditional methods. Furthermore, we conduct an initial exploration of applying multimodal models to remote sensing image quality inspection.

Key facts. No citing papers in the map yet (data through 13 Oct 2026). Builds on 19 of its 25 references that are in the map. First posted on arXiv 22 Jul 2023.

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References · 19

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7 more
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