76 datasets found

Anomaly detection is the process of identifying atypical data samples that significantly deviate from the majority of the dataset. In the realm of clinical screening and...

The Aquatic Animal Species (AAS) dataset contains 4,239 images of aquatic animals in 46 categories. Each image has 1.2 instances on average and a maximum of 22 instances.

Fundus image dataset for unsupervised domain adaptive segmentation

Fundus image dataset for unsupervised domain adaptive segmentation

The VIPSeg dataset, which is a benchmark for video scene parsing.

The Davis dataset is a benchmark for video object segmentation. It contains 30 videos with 40 frames each.

CubiCasa5K is a large-scale public dataset for floor plan image analysis.

The recognition of information in floor plan data requires the use of detection and segmentation models. However, relying on several single-task models can result in ineffective...

The FBMS dataset contains 29 training videos and 30 test videos.

Automatic segmentation of retinal vessels in fundus images plays an important role in the diagnosis of some diseases such as diabetes and hypertension.

A dataset of multiparametric MRI images of cervical cancer patients for segmentation and analysis.

The dataset in this paper comes from the database of the Ultrasound Imaging Department of Peking University Shenzhen Hospital.

A private dataset of UAV-borne remote sensing images with a resolution between 10000×10000 and 20000×20000 is constructed. Each remote sensing image which corresponds to the red...

A dataset of 99mTc-sestamibi SPECT images for automatic reorientation and segmentation of the left ventricle.

A dataset of 13N-ammonia PET images for automatic reorientation and segmentation of the left ventricle.

A dataset of 3D nuclear cardiac images for automatic reorientation and segmentation of the left ventricle.

Multimodal Brain Tumor Image Segmentation Challenge (BraTS) 2018 dataset used for brain tumor segmentation and overall survival prediction.

The dataset used for 3D fungus segmentation, consisting of 2D slices of 3D images.

The dataset used for 3D biomedical image segmentation, consisting of 2D slices of 3D images.

The CVC-ClinicDB dataset is a collection of 612 images, each with a resolution of 384x288, used for polyp diagnosis within colonoscopy videos.