… The classification is presented according to predefined classification features within the
definition of receptivity to the new: a form of knowledge of reality; leading aspects of the …

… generation of new training examples … Receptive Fields Instead of manually crafting a set of
features, multilayer perceptrons provide an adaptive approach for feature extraction by means …

… role of sparsity and localized features in a biologically-inspired model of visual object
classification. As in the … To save space, for the next 36 matches we display only the matched patch …

… study characteristics of receptive fields of units in deep convolutional networks. The receptive
… We believe this is just the start of the study of effective receptive field, which provides a new …

… Thus, the problem of producing a new material with specific characteristics (which is a problem
of construction) can, in principle, be solved through theory formation in solid state physics …

… the two-dimensional (2-D) receptive field profiles of the mam… Our next goal is to further
search for an optimal and sparse … feature vector and applying the GFC method for classification. …

… the size of feature receptive fields. … means that features deeper in the networks are equally
affected by image locations increasingly far away in both dimensions. A symmetric receptive …

… an updated definition of the term “receptivity” now included in the WHO’s Malaria Terminology
[2]) and exploration of new … to transmission—as the defining characteristic of “receptivity.” …

… in their properties as already noted. We will next turn to a number of quantitative measures
to determine to what extent the basic criteria which had been used in classifying cells might …

… a function of the number of features (which we will discuss in the next section) both with and
… In this experiment, we fixed the number of features (1600) and receptive field size (6 pixels), …