Image recolorization enhances the visual perception of an image for design and artistic
purposes. In this work, we present a deep neural network, referred to as PaletteNet, which …

The work of Levin et al.(2004) popularized stroke-based methods that add color to gray
value images according to a small amount of user-specified color samples. Even though …

Seeded segmentation methods have gained a lot of attention due to their good performance
in fragmenting complex images, easy usability and synergism with graph-based …

Multi-GANs, inspired by traditional GAN, divide each problem space into several smaller and
more homogeneous subspaces. It is an architecture of multiple generative adversarial …

Recent methods based on deep learning have shown promise in converting grayscale
images to colored ones. However, most of them only allow limited user inputs (no inputs …

This paper presents a novel colorization technique for hand-drawn grayscale images, such
as cartoons and sketches, based on reference natural images and simple user interactions …

Techniques of using convolutional neural networks (CNNs) to colorize monochrome still
images have been widely researched. However, the results of automatic colorization are …

This paper presents an interactive algorithm that is fast and accurate for segmentation of
multiclass images called GMMLC (Gaussian Mixture Model in Laplacian Coordinates). The …

Aldimir José Bruzadin Segmentação Interativa de Imagens de Tomografia
Computadorizada Pulmonar com COVID-19 via Aprendizado P Page 1 Câmpus de São …

Neste trabalho, apresentamos um novo método de segmentação interativa de imagens
baseado em aprendizado profundo, com foco em imagens médicas do pulmão de pacientes …