2 citations · 2 across the 7 of their papers we have counts for
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AgroTools: A Benchmark for Tool-Augmented Multimodal Agents in Agriculture
Zi Ye, Yibin Wen, Xiaoya Fan +10
Agricultural decision-making increasingly requires multimodal systems that can transform visual observations into reliable, executable actions. However, existing agricultural multi…
Beyond RGB: Benchmarking and Enhancing MLLMs for Hyperspectral Image Understanding via Training-Free Reasoning Framework
Xinyu Zhang, Zurong Mai, Qingmei Li +13
Multimodal Large Language Models (MLLMs) have achieved strong performance on RGB image understanding, yet their ability to use spectral evidence beyond the visible range remains la…
GALA: A GlobAl-LocAl Approach for Multi-Source Active Domain Adaptation
Juepeng Zheng, Peifeng Zhang, Yibin Wen +3
Domain Adaptation (DA) provides an effective way to tackle target-domain tasks by leveraging knowledge learned from source domains. Recent studies have extended this paradigm to Mu…
A Comprehensive Review of Agricultural Parcel and Boundary Delineation from Remote Sensing Images: Recent Progress and Future Perspectives
Juepeng Zheng, Zi Ye, Yibin Wen +7
Powered by advances in multiple remote sensing sensors, the production of high spatial resolution images provides great potential to achieve cost-efficient and high-accuracy agricu…
GTPBD: A Fine-Grained Global Terraced Parcel and Boundary Dataset
Zhiwei Zhang, Zi Ye, Yibin Wen +4
Agricultural parcels serve as basic units for conducting agricultural practices and applications, which is vital for land ownership registration, food security assessment, soil ero…
Can Large Multimodal Models Understand Agricultural Scenes? Benchmarking with AgroMind
Qingmei Li, Yang Zhang, Zurong Mai +10
Large Multimodal Models (LMMs) has demonstrated capabilities across various domains, but comprehensive benchmarks for agricultural remote sensing (RS) remain scarce. Existing bench…
Evidential Graph Contrastive Alignment for Source-Free Blending-Target Domain Adaptation
Juepeng Zheng, Yibin Wen, Jinxiao Zhang +2
In this paper, we firstly tackle a more realistic Domain Adaptation (DA) setting: Source-Free Blending-Target Domain Adaptation (SF-BTDA), where we can not access to source domain…