arXiv:2511.02831v2 Announce Type: replace
Abstract: The data for remote sensing is constantly acquired, and new data comes from a growing number and diversity of satellites, while the vast majority o...
By Hakob Tamazyan, Ani Vanyan, Alvard Barseghyan, Anna Khosrovyan, Evan Shelhamer, Hrant Khachatrian
The paper introduces SGFNet, a Semantic‑Guided Fusion Network for classifying multi‑source remote sensing images. It features a Semantic Mixing Convolution Block that generates semantic‑aware kernels based on contextual relationships, and a Frequency Modulated Fusion Block that fuses cross‑modal information in the frequency domain to mitigate spatial misalignment. Experiments on the Augsburg and Houston 2018 datasets show SGFNet consistently outperforms state‑of‑the‑art methods.
By Yuwei Zhao, Chuanzheng Gong, Baogui Huan, Feng Gao, Junyu Dong, Qian Du
The paper introduces DOD-SA, a framework for infrared-visible object detection that uses only single-modality annotations. It employs a Collaborative Teacher-Student Network with a single-modality branch and a dual-modality decoupled branch to transfer knowledge across modalities, and a Progressive and Self‑Tuning Training Strategy to refine pseudo‑labels. A Pseudo Label Assigner is also designed to align labels between modalities during training.
By Hang Jin, Chenqiang Gao, Junjie Guo, Fangcen Liu, Qinyao Chang, Kanghui Tian, Deyu Meng
arXiv:2607. 12704v1 Announce Type: cross Abstract: Multi-label classification assigns several co-occurring labels to each aerial scene, yet deployed models often encounter data distributions different from their training.
By Alaa Almouradi, Erchan Aptoula
arXiv:2610.00693v1 Announce Type: new
Abstract: Federated learning (FL) has recently attracted increasing attention in remote sensing (RS) since it enables collaborative model training across decentr...
By Bar{\i}\c{s} B\"uy\"ukta\c{s}, Beg\"um Demir
Despite the remarkable progress over the past decades, accurately identifying small objects remains challenging because of their insufficient visual cues. Previous works typically attempt to construct discriminative representation of the small objects.