Evaluating ecological time series is critical for benchmarking model performance in many important applications, including predicting greenhouse gas fluxes, tracking soil moisture and soil–atmosphere interactions, and monitoring hydrological cycles. Traditional numerical metrics (e.g., R-squared, root mean square error...
Qi Cheng, Licheng Liu, Yi-Xuan Chen et al.· Proceedings of the 32nd ACM...· 3 citations
Evaluating ecological time series is critical for benchmarking model performance in many important applications, including predicting greenhouse gas fluxes, tracking soil moisture and soil–atmosphere interactions, and monitoring hydrological cycles. Traditional numerical metrics (e.g., R-squared, root mean square error...
Qi Cheng, Licheng Liu, Yixuan Chen et al.· Proceedings of the 32nd ACM...· 0 citations
This work introduces UAV3DCrop, a public benchmark of repeated multi-angle unmanned aerial vehicle (UAV) crop surveys, and evaluates seven scene-optimized methods -- Neural Radiance Field and 3D Gaussian Splatting variants -- on held-out views, photogrammetry-referenced depth, and canopy-height recovery.
Junxiong Zhou, Xuechen Li, Chonghao Qiu et al.· 0 citations
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