Claudio Castellanos Sánchez

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Modeling visual perception of motion by connectionist networks offers various areas of research for the development of real-time models of dynamic perception-action. In this paper we present the bases of a bio-inspired connectionist approach that is part of our development of neural networks applied to autonomous robotics. Our model of visual perception of(More)
Gossypol is a natural disesquiterpene that blocks the activity of the mammalian facilitative hexose transporter GLUT1. In human HL-60 cells, which express GLUT1, Chinese hamster ovary cells overexpressing GLUT1, and human erythrocytes, gossypol inhibited hexose transport in a concentration-dependent fashion, indicating that blocking of GLUT1 activity is(More)
Visual motion provides useful information to understand the dynamics of a scene to allow intelligent systems interact with their environment. Motion computation is usually restricted by real time requirements that need the design and implementation of specific hardware architectures. In this paper, the design of hardware architecture for a bio-inspired(More)
In this paper we present a bio-inspired connectionist model for visual perception of motion and its pursuit. It is organized in three stages: a causal spatio-temporal filtering of Gabor-like type, an antagonist inhibition mechanism and a densely interconnected neural population. These stages are inspired by the treatment of the primary visual cortex, middle(More)
In this paper we propose a bio-inspired architecture to detect , describe and distinguish objects in motion. By using neuronal and physiological mechanisms in primary visual cortex (V1), middle temporal (MT) and inferotemporal (IT) areas we can start isolating the objects from their environment; then, track, label and distinguish the humans from non-human(More)