Distributed, layered and reliable computing nets to represent neuronal receptive fields

Abstract. Receptive fields of retinal and other sensory neurons show a large variety of spatiotemporal linear and non linear types of responses to local stimuli. In visual neurons, these responses present either asymmetric sensitive zones or center-surround organization. In most cases, the nature of the responses suggests the existence of a kind of distributed computation prior to the integration by the final cell which is evidently supported by the anatomy. We describe a new kind of discrete and continuous filters to model the kind of computations taking place in the receptive fields of retinal cells. To show their performance in the analysis of diferent non-trivial neuron-like structures, we use a computer tool specifically programmed by the authors to that efect. This tool is also extended to study the efect of lesions on the whole performance of our model nets.

What is the optimal stitching orientation from an aerial survey perspective?

Mosaicing is a technique that allows obtaining a large high resolution image by stitching several images together. These base images are usually acquired from an elevated point of view. Until recently, low-altitude image acquisition has been performed typically by using using airplanes, as well as other manned platforms. However, mini unmanned aerial vehicles (MUAV) endowed with a camera have lately made this task more available for small for cicil applications, for example for small farmers in order to obtain accurate agronomic information about their crop fields. The stitching orientation, or the image acquisition orientation usually coincides with the aircraft heading assuming a downwards orientation of the camera. In this paper, the efect of the image orientation in the eficiency of the aerial coverage path planning is studied. Moreover, an algorithm to compute an optimal stitching orientation angle is proposed and results are numerically compared with classical approaches.