imagenet-100/train/n01440764/n01440764_10042.JPEG 6350 2021-08-02 13:53:18 imagenet-100/train/n01440764/n01440764_10043.JPEG 68487 2021-08-02 13:53:18 imagenet-100/train/n01440764/n01440764_10048.JPEG 45206 2021-08-02 13:53:18 imagenet-100/train/n01440764/n01440764_10066.JPEG...
ImageNet-100 is a subset of ImageNet-1k Dataset from ImageNet Large Scale Visual Recognition Challenge 2012. It contains random 100 classes as specified in Labels.json file. Link: https://www.kaggle.com/datasets/ambityga/imagenet100Benchmarks Edit No benchmarks yet. Start a new benchmark...
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在三个(Caltech-256、QuickDraw和Amazon Reviews)含大量错误标签的数据集中,研究人员随机检查了部分样本(分别是8.6%、0.04%、0.02%),对其它数据集则对所有识别到的错误标签进行检查,如下表所示。(注意,由于ImageNet测试集不公开,所以这里使...
如果模型到10亿,训练ImageNet会过拟合,论文采用了自监督学习方法MAE中的预训练-微调范式对大规模ViTAE模型的训练方式进行优化,并基于此对ViTAE模型的效果进行了分析。 MAE在预训练阶段采用随机采样的图片块作为输入。这样高度稀疏的离散图片块缺失了空间连续信息,难以让NC中的卷积分支学到合适的空间特征表示。
研究人员估计10个数据集的平均错误率为3.4%,例如2916个标签错误在ImageNet中占比6%;39万个标签错误在亚马逊评论中占比4%。此外,即使在MNIST数据集——已被成千上万的同行评审用于ML研究的基准测试,在其测试集中也包含了15个(人类验证的)标签错误。
Security Insights ImageNet100#25 New issue Closed Description ChongjianGE ceezy767 commentedon Dec 19, 2019 ceezy767 ChongjianGE commentedon Dec 19, 2019 ChongjianGE ChongjianGE closed this ascompletedon Dec 19, 2019 Sign up for freeto join this conversation on GitHub.Already have an account?
ImageNet-100 实验 从下表 1 可以看出，在 ImageNet-100 数据集上，DRNet 相比于 ResNet-50，减少了 17% 的 FLOPs，同时获得了 4.0% 的准确率提升。当调整超参数和时，可以减少 32% 的 FLOPs 并提升 1.8% 准确率。另外，采用分辨率感知的 BN 获得了性能提升而 FLOPs 相似。表 1 ：ResNet-50 骨干...
Hi @HobbitLong, thanks for your great work and also sharing the code. I guess the ImageNet-100 is not a conventional subset so I wonder if you can share the list since we also don't have enough resources to run on the full ImageNet ==.
main data data_uq_idxs model splits util LICENSE README.md config.py logits_adj_utils.py pipeline.png run_cifar10.sh run_cifar100.sh run_imagenet100.sh Breadcrumbs BaCon / Latest commit Cannot retrieve latest commit at this time.