A study of 2D features for 3D visual SLAM

Paper submitted to the 43rd International Symposium on Robotics (ISR), Taipei, Taiwan, August 29-31, 2012.

A neural network algorithm to simplify 2D meshes

In this paper we propose a neural network model to simplify and 2D meshes. This model is based on the Growing Neural Gas model and is able to simplify any mesh with different topologies and sizes. A triangulation process is included with the objective to reconstruct the mesh. This model is applied to some problems related to urban networks.

Representation of 2D objects with a topology preserving network

Comunicación presentada en el 2nd International Workshop on Pattern Recognition in Information Systems, Alicante, April, 2002.

Ordered porous nanomaterials: the merit of small

This paper will introduce the reader to some of the “classical” and “new” families of ordered porous materials which have arisen throughout the past decades and/or years. From what is perhaps the best-known family of zeolites, which even now to this day is under constant research, to the exciting new family of hierarchical porous materials, the number of strategies, structures, porous textures, and potential applications grows with every passing day. We will attempt to put these new families into perspective from a synthetic and applied point of view in order to give the reader as broad a perspective as possible into these exciting materials.