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Transferring the knowledge learned from large scale datasets (e.g., ImageNet) via fine-tuning offers an effective solution for domain-specific fine-grained visual categorization (FGVC) tasks (e.g., recognizing bird species or car make and model).
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https://www.kaggle.com/c/inaturalist-challenge-at-fgvc-2017
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O. Mac Aodha, S. Su, Y. Chen, P. Perona, and Y. Yue · 2018
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The inaturalist species classification and detection dataset
G. Van Horn, O. Mac Aodha, Y. Song, Y. Cui, C. Sun, A. Shepard, H. Adam, P. Perona, and S. Belongie · 2018
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Deep layer aggregation
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Learning transferable architectures for scalable image recognition
B. Zoph, V. Vasudevan, J. Shlens, and Q. V. Le · 2018
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