Change detection is an important topic in remote sensing to study the effects of climate change, natural disasters, urbanization, etc. However, the need for labeled data has posed significant challenges. In this paper, we introduce a self-supervised learning model to overcome this problem. To evaluate our model performance, we propose a novel evaluation metric called recall-based operational reliability. In our study, we used a large-scale multispectral image dataset called DynamicEarthNet for testing.
Large Scale Multispectral Image Dataset Change Detection Based on Self-Supervised Learning with Novel Evaluation Metric
2024-07-15
2220121 byte
Conference paper
Electronic Resource
English
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