262 datasets found

The Fifteen Natural Scene Categories database is used for bag-of-features based image classification problem.

The CRC dataset contains images of colorectal cancer histology.

The BACH dataset contains images of breast cancer histology.

The Breast Cancer Histopathological Image Classification dataset contains images of breast cancer histopathology.

A novel benchmark for multi-label image classification in medical imaging, combining new classes and domains into a challenging scenario.

A dataset used for testing the proposed Deep Feature Learning method for histopathology image classification.

A dataset used for training and testing the proposed Deep Feature Learning method 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...

The dataset used in this paper for image annotation, consisting of 4,999 annotated images with a vocabulary of up to 200 keywords.

The MNIST data set is a dataset used for testing the performance of the DisDF.

The dataset used in the paper for hyper-parameter tuning using transient cloud resources.

A large-scale benchmark archive for remote sensing image classification and retrieval.

Caltech-UCSD Birds (CUB 200-2007) and extended version CUB 200-2011 image collections tagged with keypoints, bounding boxes, coarse segmentation, and attribute labels.

The TerraIncognita dataset consists of 24,778 samples from four domains: painting, sketch, cartoon, and photo.

The dataset used in the paper is a custom dataset for image classification tasks, featuring images with varying sizes and resolutions.

The dataset used in the paper is a custom dataset for image classification tasks, featuring images with varying sizes and resolutions.

The dataset used in the paper is a multi-task learning dataset, where the goal is to learn a shared feature extractor and a task-specific predictor for multiple tasks.

A synthetic image dataset for evaluating Concept Bottleneck Models (CBMs) with perfect concept annotations.

Birdsnap is a dataset for fine-grained bird species classification.

99 images of benign and malignant thyroid nodules for classification