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Found 5 papers, 1 papers with code
A multi-stage GAN for multi-organ chest X-ray image generation and segmentation
Multi-organ segmentation of X-ray images is of fundamental importance for computer aided diagnosis systems.
Deep Dynamic Factor Models
A novel deep neural network framework -- that we refer to as Deep Dynamic Factor Model (D$^2$FM) --, is able to encode the information available, from hundreds of macroeconomic and financial time-series into a handful of unobserved latent states.
Weak Supervision for Generating Pixel-Level Annotations in Scene Text Segmentation
Providing pixel-level supervisions for scene text segmentation is inherently difficult and costly, so that only few small datasets are available for this task.
A Two Stage GAN for High Resolution Retinal Image Generation and Segmentation
In this paper, we use Generative Adversarial Networks (GANs) for synthesizing high quality retinal images, along with the corresponding semantic label-maps, to be used instead of real images during the training process.
COCO_TS Dataset: Pixel-level Annotations Based on Weak Supervision for Scene Text Segmentation
The generated annotations are used to train a deep convolutional neural network for semantic segmentation.
