Machine Learning and image processingy

Machine Learning is the branch of artificial intelligence whose objective is the development of techniques that allow computers to learn from data. This research field is undergoing an extraordinary revolution and popularization thanks to a family of techniques called Deep Learning. These are computational models composed of numerous processing layers, and used to learn representations with multiple levels of abstraction from input data. These methods, during the last decade, have drastically improved the results provided by existing techniques in tasks such as speech recognition, machine translation and image classification, and have directly exceeded human capacity in complex activities (such as winning human champions playing Go). Among all the applications of deep learning, there is one that is particularly noteworthy for the large amount of existing work and the amazing results obtained: computer vision and image processing. In fact, one of the most effective forms of deep learning (convolutional neural networks) has largely surpassed pre-existing techniques in object detection and face recognition, just to name two examples.

The main goal of this research line is to create new theoretical and practical developments in the field of image analysis through machine learning techniques. From a practical point of view, fully connected, convolutional, recurrent and generative adversarial networks, among others, are employed to solve complex real-world problems. Application areas include medical diagnosis, forensic identification, metallurgical industry, and human-robot interaction, just to name a few. From the theoretical and methodological point of view, the aim is to study the properties and empirical performance of existing models, as well as to analyze, design, implement and validate new learning approaches that can make a novel and original contribution to the state of the art.

Responsible: Pablo Mesejo Santiago

Investigadores relacionados:

Letra:

  Name Email Area Cat.
Ortíz García, Andrés aortiz@ic.u1L6AgDlenrpMma.es DaSCI Technology Applications Area PhD
Salas González, Diego dsalas4DaH5wG.dwI_@ugr.es DaSCI Technology Applications Area PhD
Martínez Murcia, Francisco Jesús fjesusmartinez@uBRzzSFHfugr.es DaSCI Technology Applications Area PhD - Juan de la Cierva
Segovia Román, Fermín fsegovia@ugr.8JB_hvFYCes DaSCI Technology Applications Area PhD
Górriz Sáez, Juan Manuel gorriz@BjAE@Kf3ugr.es DaSCI Technology Applications Area PhD
Ramírez Pérez de Inestrosa, Javier javierrp@ugraxnNANrXaJDy.es DaSCI Technology Applications Area PhD
Mesejo Santiago, Pablo pablomesejo@gB98UCQ1Phmail.com DaSCI Technology Applications Area PhD - Marie Curie
Villar Castro, Pedro pvillarc@ugr.tl4.rLOG0puses Data Science and Big Data Area PhD
Gutiérrez Salcedo, Salvador salvador.gutierrez@ucabgGxI4lbK.es Data Science and Big Data Area PhD
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