A Neural Algorithm of Artistic Style

In fine art, especially painting, humans have mastered the skill to create unique visual experiences through composing a complex interplay between the content and style of an image. Thus far the algorithmic basis of this process is unknown and there exists no artificial system with similar capabilities. However, in other key areas of visual perception such as object and face recognition near-human performance was recently demonstrated by a class of biologically inspired vision models called Deep Neural Networks. Here we introduce an artificial system based on a Deep Neural Network that creates artistic images of high perceptual quality. The system uses neural representations to separate and recombine content and style of arbitrary images, providing a neural algorithm for the creation of artistic images. Moreover, in light of the striking similarities between performance-optimised artificial neural networks and biological vision, our work offers a path forward to an algorithmic understanding of how humans create and perceive artistic imagery

Deep learning y big data en cartografía digital. Creación de inteligencias artificiales para el tratamiento de ortofotografías y sistemas de información geográfica tridimensionales

Tesis Doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Filosofía y Letras. Departamento de Geografía. Fecha de Lectura: 16-07-202

Comparing users preferences with landscape planning and management proposals at regional level – tourism sector

Landscape European Convention considers landscape an important part of quality of life for people everywhere and its protection, management and planning entail rights and responsibilities for everyone. In this sense, landscape planning should go beyond technician approaches or legal frameworks to also involve people in the processes. This raises the question of using the results from scientific knowledge developed by different methods to the design of proposals for territorial and sectorial institutional planning – moving into action to transdisciplinarity. This paper addresses this issue as it bridges across the results of a landscape preference survey for tourists in the Alentejo region (included in the ROSA project) and the landscape planning and management proposals for tourism in the Regional Strategic Plan for Alentejo-PROTAL. The results obtained can lead to the adjustment of PROTAL strategies and/or proposed land uses, improving the planning process to include people preferences