Sentence examples for maps from input from inspiring English sources

Recently Saliency maps from input images are used to detect interesting regions in images/videos and focus on processing these salient regions.

To achieve this, we propose SalClassNet, a CNN framework consisting of two networks jointly trained: a) the first one computing top-down saliency maps from input images, and b) the second one exploiting the computed saliency maps for visual classification.

It can achieve the arbitrary nonlinear mapping from input to output.

The driving sequence u k only influences the algorithmic mapping from input to output.

Experimental results demonstrate that our operator, with the use of appropriate threshold values, may produce an edge map from input data.

With this type of architecture, the mapping from input space (i.e., visual words) to latent topics can be done by a simple matrix multiplication.

Supervised machine learning is the most common technique, where the aim is to derive a mapping from input x to output y, given a labeled set of input output pairs [11].

By assigning activation to each of the input node and allowing them to propagate through the hidden layer nodes to the output nodes, neural network performs a functional mapping from input values to output values.

Fig. 2 This figure illustrates different approaches of using the kernel in combination with SVM. a When data samples from different classes are not linearly separable, they are mapped from input space to higher even infinite dimension Hilbert space.

A typical example is classification, where the goal is to learn a mapping from input data ({mathbf x }) to output data y, where (y = {1,ldots,C}), with C being the number of classes.

GF-discrepancy based point set is employed to exploit the hidden low-dimensional structure in the mapping from input to the quantity of interest (QOI), a kriging metamodel (Kaymaz, 2005) with higher accuracy and efficiency can be constructed on the low-dimensional subspace.