Frequency-Aware Vision-Language Multimodality Generalization Network for Remote Sensing Image Classification

A new method called Noise-Adaptive Regularization (NAR) has been proposed to improve multi-label classification in remote sensing, addressing the challenges posed by noisy annotations that can arise from cost-effective data collection methods. NAR distinguishes between additive and subtractive noise within a semi-supervised learning framework, enhancing the robustness of image classification.