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Improving image classification with location context
Improving image classification with location context. -
YFCC100M-GEO100
The YFCC100M-GEO100 dataset contains 100,000 images with 100,000 geotags. -
Benchmarking representation learning for natural world image collections
Benchmarking representation learning for natural world image collections. -
Animals with Attributes (AwA)
Zero-shot learning (ZSL) aims to classify objects that are not observed or seen during training. It relies on class semantic description to transfer knowledge from the seen... -
CottonCultivar and SoyCultivarLocal datasets
Two public leaf datasets are used in this experiment. The training and testing sets are split with a ratio of 1:1 for model evaluation. The CottonCultivar dataset contains 80... -
MIT Places
MIT Places dataset, a dataset of images of places. -
iNaturalist 2018 dataset
The dataset used in the paper is the iNaturalist 2018 dataset, which is a real-world large-scale imbalanced dataset. -
TNCD: Thyroid Nodule Classification Dataset
Thyroid Nodule Classification Dataset (TNCD) is a benchmark for thyroid nodule diagnosis, containing 3493 ultrasound images taken from 2421 patients. -
CIFAR-10 and GIST1M datasets
The dataset used in this paper is CIFAR-10 and GIST1M. -
edges2shoes
A dataset of 10 simple object classes (pineapple, soccer, basketball, etc.) with white backgrounds. -
Deep Neural Networks for Pattern Recognition
The dataset used for training and testing the conditional generative adversarial networks for pattern recognition. -
Machine Recognition of Crystallization Outcomes (MARCO)
The MARCO dataset contains 493,214 scored images from five institutions, with images collected from imagers made from two different manufacturers and in-house imaging equipment. -
SLICE dataset
The SLICE dataset contains images of slices of cheese. -
Agri-ImageNet
Agricultural image dataset used to evaluate the proposed HaST-CW model. -
mediamill dataset
The mediamill dataset consists of 43,907 examples. Each example has 120 features and belongs to one or multiple of the 101 classes. -
Fifteen Natural Scene Categories
The Fifteen Natural Scene Categories database is used for bag-of-features based image classification problem. -
MIDOG21 Dataset
A dataset used for testing the proposed Deep Feature Learning method for histopathology image classification. -
In-House Dataset
A dataset used for training and testing the proposed Deep Feature Learning method for histopathology image classification. -
Evaluation dataset for histopathology image classification
A dataset composed of 35334 breast histopathology images at zoom x5 (1.76 µm per pixel) distributed amongst 23 imbalanced classes, which include both common tumor and benign...