python dataset.py Training Use train.py to do train process, for convenience all args can be specified in config.py and use default in args. train withbachsize=256on4gpus, only take about8mins every epoch. e.g. cd experiments/ python train.py --gpu 4,5,6,7 --d 18 --mode resnet...
Contextual Label Smoothing with a Phylogenetic Tree on the iNaturalist 2018 Challenge DatasetContextual LabelSmoothingPhylogeneticRecognition of fine-grained visual categories (FGVC) in the natural world is a long-tailed problem, meaning recognizers must accurately recognize a large diversity of categories ...
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), and so on. The iNat dataset is highly ...
2018 fixing a few more links 4年前 2019 fixing a few more links 4年前 2021 fixing some typos 4年前 eval column name changes 8年前 .gitignore added AWS S3 dataset links for 2017 and 2018 5年前 LICENSE Initial commit 8年前 README.md ...
This document describes the details and the motivation behind a new dataset we collected for the semi-supervised recognition challenge~\cite{semi-aves} at the FGVC7 workshop at CVPR 2020. The dataset contains 1000 species of birds sampled from the iNat-2018 dataset for a total of nearly 150...
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...
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. ...
Open AccessArticle by Benjamin Cull Department of Entomology, College of Food, Agricultural and Natural Resource Sciences, University of Minnesota, St. Paul, MN 55108, USA Insects2025,16(2), 128;https://doi.org/10.3390/insects16020128 Submission received: 24 December 2024/Revised: 23 January 2025...