LULC-SegNet: Enhancing Land Use and Land Cover Semantic Segmentation with Denoising Diffusion Feature Fusion

LULC-SegNet: Enhancing Land Use and Land Cover Semantic Segmentation with Denoising Diffusion Feature Fusion

Deep convolutional networks often encounter information bottlenecks when extracting land object features, resulting in critical geometric information loss, which impedes semantic segmentation capabilities in complex geospatial backgrounds. We developed LULC-SegNet, a semantic segmentation network fo...

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Bibliographic Details
Main Authors: Zongwen Shi, Junfu Fan, Yujie Du, Yuke Zhou, Yi Zhang
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Remote Sensing
Subjects:
land use and land cover
semantic segmentation
remote sensing images
denoising diffusion probabilistic model
feature fusion
K-means clustering algorithms
Online Access:https://www.mdpi.com/2072-4292/16/23/4573
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