MAE self-supervised pre-training on 54,571 unlabeled grapevine images improves downstream 43-class variety classification (F1 0.7956) over ImageNet-initialized baselines, and the paper releases two multi-season labeled benchmarks.
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Advancing Image-Based Grapevine Variety Classification with a New Benchmark and Evaluation of Masked Autoencoders
MAE self-supervised pre-training on 54,571 unlabeled grapevine images improves downstream 43-class variety classification (F1 0.7956) over ImageNet-initialized baselines, and the paper releases two multi-season labeled benchmarks.