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Cells enter senescence, a state of stable proliferative arrest, in response to a variety of cellular stresses, including telomere erosion, DNA damage, and oncogenic signaling, which acts as a barrier against malignant transformation in vivo. To identify genes controlling senescence, we conducted an unbiased screen for small hairpin RNAs that extend the life(More)
Keywords: Machine vision Image segmentation Texture identification in crops Automatic tasks in agriculture a b s t r a c t One important issue emerging strongly in agriculture is related with the automatization of tasks, where the optical sensors play an important role. They provide images that must be conveniently processed. The most relevant image(More)
We present a novel strategy for computing disparity maps from hemispherical stereo images obtained with fish-eye lenses in forest environments. At a first segmentation stage, the method identifies textures of interest to be either matched or discarded. This is achieved by applying a pattern recognition strategy based on the combination of two classifiers:(More)
This paper describes a novel feature-based stereovision matching process based on a pair of omnidirectional images in forest stands acquired with a stereovision sensor equipped with fish-eye lenses. The stereo analysis problem consists of the following steps: image acquisition, camera modelling, feature extraction, image matching and depth determination.(More)
In this paper we propose a new method for combining simple classifiers through the analogue Hopfield Neural Network (HNN) optimization paradigm for classifying natural textures in images. The base classifiers are the Fuzzy clustering (FC) and the parametric Bayesian estimator (BP). An initial unsupervised training phase determines the number of clusters and(More)