@misc{10481/66493,
year = {2021},
url = {http://hdl.handle.net/10481/66493},
abstract = {Motivated by the success of DL-based models in image and video problems, in this
dissertation, we develop DL-models for challenging image and video formation and interpretation
tasks. These are image and video SR, BID, threat detection in PMMWIs
and mitosis detection in Whole-Slide Images (WSIs). In this thesis, one common point
to all contributions is the use of domain knowledge to improve the solution by developing
and applying specialized architectures, regularizations and restrictions. In the next
subsections, we present the tasks that we have addressed in this dissertation. Next,
we provide a brief introduction to the main DL-based models used in this dissertation:
CNNs and Generative Adversarial Networks (GANs). Finally, we present the objectives
of this work and the structure of the remainder of this dissertation.},
organization = {Tesis Univ. Granada.},
organization = {Spanish Ministry of Economy and Competitiveness through project DPI2016-77869-C2-2-R and the Visiting Scholar program at the University of Granada},
publisher = {Universidad de Granada},
keywords = {Deep learning},
keywords = {Image processing},
keywords = {Video processing},
title = {Modelos de Aprendizaje Profundo para el Procesamiento y Clasificación de Imágenes y Vídeo},
author = {López Tapia, Santiago},
}