1 citations · 1 across the 5 of their papers we have counts for
5 papers
Think and Answer ME: Benchmarking and Exploring Multi-Entity Reasoning Grounding in Remote Sensing
Shuchang Lyu, Haiquan Wen, Guangliang Cheng +5
Recent advances in reasoning language models and reinforcement learning with verifiable rewards have significantly enhanced multi-step reasoning capabilities. This progress motivat…
Deep Learning Based Domain Adaptation Methods in Remote Sensing: A Comprehensive Survey
Shuchang Lyu, Qi Zhao, Zheng Zhou +6
Domain adaptation is a crucial and increasingly important task in remote sensing, aiming to transfer knowledge from a source domain a differently distributed target domain. It has…
Adversarial Versus Federated: An Adversarial Learning based Multi-Modality Cross-Domain Federated Medical Segmentation
You Zhou, Lijiang Chen, Shuchang Lyu +7
Federated learning enables collaborative training of machine learning models among different clients while ensuring data privacy, emerging as the mainstream for breaking data silos…
Joint-Optimized Unsupervised Adversarial Domain Adaptation in Remote Sensing Segmentation with Prompted Foundation Model
Shuchang Lyu, Qi Zhao, Guangliang Cheng +4
Unsupervised Domain Adaptation for Remote Sensing Semantic Segmentation (UDA-RSSeg) addresses the challenge of adapting a model trained on source domain data to target domain sampl…
BEARD: Benchmarking the Adversarial Robustness for Dataset Distillation
Zheng Zhou, Wenquan Feng, Shuchang Lyu +3
Dataset Distillation (DD) is an emerging technique that compresses large-scale datasets into significantly smaller synthesized datasets while preserving high test performance and e…