Nature Multi View (NMV) Dataset Datacard To encourage development of better machine learning methods for operating with diverse, unlabeled natural world imagery, we introduce Nature Multi View (NMV), a multi view dataset of over 3 million ground level and aerial image pairs from over 1.75 million citizen science observations for over 6,000 native and introduced plant species across California. Characteristics and Challenges Long Tail Distribution: The dataset exhibits a long tail distribution common in natural world settings, making it a realistic benchmark for machine learning applications. Geographic Bias: The dataset reflects the geographic bias of citizen science data, with more observations from densely populated and visited regions like urban areas and National Parks. Many to One Pairing: There are instances in the dataset where multiple ground level images are paired to the same aerial image. Splits Training Set: Full Training Set: 1,755,602 observations, 3,307,025 images Labeled Training Set: 20%: 334,383 observations, 390,908 images 5%: 93,708 observations, 97,727 images 1%: 19,371 observations, 19,545 images 0.25%: 4,878 observations, 4,886 images Validation Set: 150,555…
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