Algorithms from statistical physics for generative models of images

Improvement of generative adversarial networks for automatic text-to-image generation

This research is related to the use of deep learning tools and image processing technology in the automatic generation of images from text. Previous researches have used one sentence to produce images. In this research, a memory-based hierarchical model is presented that uses three different descriptions that are presented in the form of sentences to produce and improve the image. The proposed ...

A Statistical Model of Texture for Medical Image Synthesis and Analysis

We address the problem of building generative statistical models of the appearance of highly variable medical images, in particular mammograms. We treat appearance as a texture that can vary over the image plane. We present a model motivated by one of the most successful algorithms in the texture synthesis literature. Our approach has significant advantages over existing methods: it can learn f...

Segmentation of Photospheric Solar Images by Using c-Means,k-Means, and FCM Algorithms

Automatic Colorization of Grayscale Images Using Generative Adversarial Networks

Automatic colorization of gray scale images poses a unique challenge in Information Retrieval. The goal of this field is to colorize images which have lost some color channels (such as the RGB channels or the AB channels in the LAB color space) while only having the brightness channel available, which is usually the case in a vast array of old photos and portraits. Having the ability to coloriz...

Biomedical Image Denoising Based on Hybrid Optimization Algorithm and Sequential Filters

Background: Nowadays, image de-noising plays a very important role in medical analysis applications and pre-processing step. Many filters were designed for image processing, assuming a specific noise distribution, so the images which are acquired by different medical imaging modalities must be out of the noise. Objectives: This study has focused on the sequence filters which are selected ...