The iNaturalist 2017 dataset (iNat) contains 675,170 training and validation images from 5,089 natural fine-grained categories. Those categories belong to 13 super-categories including Plantae (Plant), Insecta (Insect), Aves (Bird), Mammalia (Mammal), an
The iNat Challenge 2017 dataset contains 5,089 species, with a combined training and validation set of 675,000 images that have been collected and verified by multiple users from inaturalist.org. The dataset features many visually similar species, captured in a wide variety of situations, from ...
iNaturalist Research-grade observations [Occurrence dataset] Retrieved from https://www.gbif.org/dataset/50c9509d-22c7-4a22-a47d-8c48425ef4a7 (2023) Google Scholar Ioannides et al., 2015 K. Ioannides, K. Stamoulis, C. Papachristodoulou, E. Tziamou, C. Markantonaki, I. Tsodoulos Dis...
In contrast to other image classification datasets such as ImageNet, the dataset in the iNaturalist challenge exhibits along-tailed distribution, with many species having relatively few images. It is important to enable machine learning models to handle categories in the long-tail, as the natural wo...
. Geographical occurrences of IAS observed on iNaturalist to the end of 2023 were then compared at the equivalent NUTS2/3 regional scale to the VectorNet project’s mosquito maps published in October 2023 [30] by recording the presence or absence of IAS in each regional unit for each dataset...
added AWS S3 dataset links for 2017 and 2018 5年前 LICENSE Initial commit 8年前 README.md updating download links for all competitions 4年前 README MIT iNaturalist Competition Datasets Current Competitions 2021 Competition Previous Competitions ...
The iNat Challenge 2017 dataset contains 5,089 species, with a combined training and validation set of 675,000 images that have been collected and verified by multiple users from inaturalist.org. The dataset features many visually similar species, captured in a wide variety of situations, from ...