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Sponsored Artificial Intelligence: A Modern Approach, Global Edition Artificial Intelligence: A Modern Approach, Global Edition

Author

Jia-Qi Zhao

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2026

AMS-SemiCD: A Synergistic Framework for Semisupervised Change Detection via an Adaptive Pseudolabeling Strategy and a Multibranch Network

Semisupervised change detection (SSCD) aims to reduce the dependence on extensive labeled data. However, existing methods face three critical challenges. First, class imbalance and boundary ambiguity induce class-dependent confidence distributions, hindering reliable pseudolabel selection. Second, uncertain pixels may...

Di Zhang, Pei-Cheng Yue, Hui-Fang Ma et al. · 0 citations
Preprint Sep 2026

A Unified Framework and Dataset for Oriented Object Visual Grounding in Remote Sensing

Visual grounding in remote sensing images aims to locate objects described by referring expressions. Most existing methods predict horizontal bounding boxes, which are often inaccurate for objects with arbitrary orientations. To address this limitation, we introduce O$^2$-VG, a family of models for oriented object visu...

Ze-Yu Ding, Yong Zhou, Jia-Qi Zhao et al. · 0 citations
2026

Focused Adapter: Enhancing Fine-Grained Attention for Remote Sensing Image–Text Retrieval

The emergence of large-scale vision–language models (VLMs) has significantly advanced remote sensing image–text retrieval (RSITR) by providing powerful cross-modal semantic priors. However, when adapted to the remote sensing (RS) domain, these models struggle to capture fine-grained representations due to their inheren...

Wen-Liang Du, Xiao-Yu Xu, Jia-Qi Zhao et al. · 0 citations
2026

Toward Zero-Forgetting: A Training-Free Multimodal Framework for Remote Sensing Class-Incremental Learning

Existing class-incremental learning (CIL) methods for remote sensing (RS) scene classification often tend to be training-intensive or rely on static visual features that may inadequately capture the complex interclass similarity and intraclass diversity inherent in RS imagery. Moreover, directly reusing features from m...

Wen-Liang Du, Ji-Cun He, Jia-Qi Zhao et al. · 0 citations

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