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Bumble Bee Species Image Classification
Bumble bee species image classification dataset -
ISLVRC2012
The dataset used in the paper is ISLVRC2012, a dataset for image classification. -
ResNest: Split-attention networks
ResNest: Split-attention networks. -
Colored MNIST dataset
The dataset used in the paper is a binary classification task in a 300-dimensional space. The procedure for generating the training dataset is as follows: Each label y ∈ {−1, 1}... -
ImageNet32x32
The dataset used in the paper is ImageNet32x32, a down-sampled version of ImageNet. -
YFCC100M dataset
The YFCC100M dataset. -
ImageNet-2012 training set
The ImageNet-2012 training set of 1.2 million images labelled into 1,000 object categories. -
MultiGrain
MultiGrain is a network architecture producing compact vector representations that are suited both for image classification and particular object retrieval. -
Oxford Flower-102
Fine-grained image classification, which aims to recognize subordinate level categories, has emerged as a popular research area in the computer vision community. -
iNaturalist 2021-mini dataset
The iNaturalist 2021-mini dataset contains images of animals from 200 species. -
CUB dataset
The CUB dataset is a large collection of images of birds, each image is a 299x299 RGB image, and there are 11,778 training images and 5,994 testing images. -
rotated MNIST, CIFAR-10, and PatchCamelyon
The dataset used in the paper is not explicitly described. However, it is mentioned that the authors used the rotated MNIST, CIFAR-10, and PatchCamelyon datasets. -
Very Deep Convolutional Networks for Large-Scale Image Recognition
The dataset consists of 60,000 images of objects in 200 categories, with 300 images per category. -
MNIST and CIFAR-10
The MNIST dataset is a large dataset of handwritten digits, and the CIFAR-10 dataset is a dataset of images from 10 different classes. -
MobileNetV1, MobileNetV2 and MNasNet models for ImageNet classification
The dataset used in this paper is the MobileNetV1, MobileNetV2 and MNasNet models for ImageNet classification. -
ImageNet, ADE20K, and COCO datasets
The dataset used for ImageNet recognition, ADE20K semantic segmentation, and COCO panoptic segmentation.
