Dynamic Earth observation applications often require land-cover segmentation models to recognize newly emerging classes from only a few pixel-level annotations while retaining previously learned knowledge. However, gradient-based incremental fine-tuning (FT) is prone to severe overfitting and catastrophic forgetting un...
Han-Yuan Ge, Bo Ren, Junxi Guo et al.· IEEE Transactions on Geoscie...· 0 citations
In remote-sensing scene classification (RSSC), persistent challenges such as high interclass similarity and substantial intraclass diversity remain key obstacles to accurate recognition. Although vision Transformer (ViT) has demonstrated outstanding performance, it tends to smooth out high-frequency discriminative deta...
Hui-Hui Dong, Tong Wang, Zong-Fang Ma et al.· IEEE Transactions on Geoscie...· 0 citations
Joint classification of multispectral (MS) and panchromatic (PAN) imagery has achieved remarkable success, aiming to provide more detailed and accurate interpretations of ground objects. However, when labeled samples are insufficient, the generalization performance of deep learning-based methods can be significantly af...
Xiao-Tong Li, Wan-Ling Gao, Jia-Qi Si et al.· IEEE Transactions on Geoscie...· 0 citations
To relieve the problems of the lack of semantic alignment in the geometric representation space and insufficient modality-specific instruction calibration in infrared-visible image fusion (IVIF), we first propose a dynamic instruction-aware geometric representation (DIGR) for IVIF, which achieves semantic alignment bet...
Mengru Ma, Yong-Zhe Wang, Wen-Ping Ma et al.· IEEE Transactions on Geoscie...· 0 citations
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