10 datasets found

Biomedical image analysis, data augmentation, Generative Adversarial Networks (GANs), synthetic images

Biomedical image analysis, data augmentation, Generative Adversarial Networks (GANs), synthetic images

The MedMNIST dataset is a large standardized biomedical image collection, including 12 number of 2D datasets and 6 number of 3D datasets.

SynArtifact-1K is a comprehensive dataset of synthetic images with artifact annotations, constructed to fine-tune Vision-Language Model (VLM) as artifact classifier.

The commonly used benchmark for image deblurring is Go-Pro (Nah, Kim, and Lee 2017), where the input blurry images are synthetic.

The dataset used in this paper for multi-sensor next-best-view planning as matroid-constrained submodular maximization.

The SynthBuster dataset is a collection of images generated by various diffusion models.

The dataset used in the paper for image denoising, consisting of 50 scenarios.

SynthText dataset is proposed by Gupta et al. for scene text detection. The original dataset is composed of 800,000 scene text images, each with multiple word instances.

The dataset used for training and validation of the proposed approach to combine semantic segmentation and dense outlier detection.