Nowadays, many visualization and imaging systems generate complex visual contents with a large amount of data, making the data extremely difficult to handle. This growing mass of data requires new strategies for data analysis and interpretation. In recent years, particular attention has been paid to deep learning methods for visual contents analysis and applications. Inspired by artificial intelligence, mathematics, biology and other fields, these methods can find relationships between different categories of complex data and provide a set of tools for analyzing and handling visual contents.
This Special Issue will provide a forum to publish original research papers covering state-of-the-art, new algorithms, methodologies, applications, theories and implementations of deep learning methods for visual contents, such as image, video, stereoscopic images, 3D meshes, points clouds, visual graphs, etc.
Deadline for manuscript submissions: 31 January 2021
Prof. Dr. Hocine Cherifi
LE2I, University of Burgundy, UMR
6306 CNRS, Dijon, France
Prof. Dr. Mohammed El Hassouni
LRIT, FLSHR, Mohammed V
University in Rabat, Rabat,
(c) GdR 720 ISIS - CNRS - 2011-2020.