Highlights of this article include: (1) proposing a novel unsupervised binary CD method that presents better performance; (2) proposing an advanced sample ...
Compared with supervised CD methods, unsupervised methods are more popular, since they can identify changes automatically.
Mar 22, 2022 · First, a pre-trained CNN is employed to produce deep features of two images, and a pseudo change map is yielded based on change vector analysis.
Mar 25, 2023 · The experimental results on both VHR optical and SAR images demonstrate the superiority and effectiveness of the proposed method. Keywords:.
This paper presents a novel object-based approach for unsupervised change detection with focus on individual buildings. First, a principal component analysis ...
This paper presents a method of detecting land cover changes in high-spatial-resolution remote sensing imagery.
It combines spatial-spectral feature analysis and metric learning to ensure that the resulting CD maps are satisfactory. Furthermore, training with the joint CD.
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The proposed approach consists of three steps, including: (1) change vector produced in posterior probability space, (2) binary change detection via TLCVA, and ...
Unsupervised change detection based on image reconstruction loss ...
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The approach effectively detects changes without relying on labelled data, making it suitable for situations where obtaining such data is challenging. However, ...
This work proposes a dual path denoising network (DPDNet) for SAR image change detection and introduces the random label propagation to clean the label ...