Logistic regression on frozen DINOv3 features achieves 88.5% macro F1 on the AQUA20 marine species benchmark, matching end-to-end supervised models with only 6% of the labels.
Aquaticclip: A vision-language foundation model for underwater scene analysis
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A systematic survey of over 200 works on deep learning and AI techniques for crops, fisheries, and livestock in agriculture.
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Label-efficient underwater species classification with logistic regression on frozen foundation model embeddings
Logistic regression on frozen DINOv3 features achieves 88.5% macro F1 on the AQUA20 marine species benchmark, matching end-to-end supervised models with only 6% of the labels.
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AI in Agriculture: A Survey of Deep Learning Techniques for Crops, Fisheries and Livestock
A systematic survey of over 200 works on deep learning and AI techniques for crops, fisheries, and livestock in agriculture.