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New benchmark compares visual backbones for solar irradiance forecasting

By PulseAugur Editorial · [1 sources] ·

A new research paper introduces a controlled benchmark for evaluating visual backbones in multimodal short-term solar irradiance forecasting. The study fixes the overall forecasting pipeline and isolates the visual backbone for comparison, testing models like ConvNeXt, Swin Transformer, and various Mamba-based architectures. Results on Folsom and NREL datasets show that while all evaluated backbones improve over smart persistence, specific models like VMamba Small and Swin Base achieve competitive RMSE values, though smart persistence remains strongest on the NREL split. AI

IMPACT Provides a standardized method for comparing visual backbones in AI-driven forecasting applications.

RANK_REASON Research paper introducing a new benchmark and evaluation of models. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New benchmark compares visual backbones for solar irradiance forecasting

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Research paper introducing a new benchmark and evaluation of models. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Oshadha Samarakoon, Dushan Herath, Ishara Ranmandala, Dilshara Herath, Roshan Godaliyadda, Parakrama Ekanayake, Vijitha Herath ·

    A Controlled Visual-Backbone Benchmark for Multimodal Short-Term Solar Irradiance Forecasting

    arXiv:2607.23633v1 Announce Type: cross Abstract: Sky-image irradiance studies often compare forecasting systems in which the image encoder, temporal model, fusion block, target definition, and training recipe all change together. We use a narrower protocol: the multimodal foreca…

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