BLMRS: A Balanced Learning Method for Multimodal Remote Sensing Image Classification (opens in new tab)

The multimodal remote sensing image classification provides essential support for fine-grained understanding of the Earth’s surface by fusing the complementary information. Yet, the multimodal fusion often suffers from a modal imbalance problem, where applying a uniform optimization objective leads to the under-optimization of certain modalities, posing a bottleneck to realizing the full benefits of fusion. Existing balanced learning strategies attempt to solve this problem by emphasizing the...