Sentence examples for weight map from inspiring English sources

To simulate the human visual system selecting processes, the final weight map is found to be an equilibrium distribution of all weighted location maps calculated by weighted dissimilarity.

Next, the computation of a scalar weight map is explained.

Next, the Gaussian pyramid of the weight map is computed.

Fig. 8 The chosen network stations on the weight map.

The detection-weight map of the original image should be consistent with the weight map of the reconstructed image.

Step 2: For each image obtain the scalar weight map (Equation 5) and the normalized scalar weight map using (Equation 6).

A weighted signed digraph G = (V, E, φ, γ) contains additionally a weight mapping γ : E → ℜ≥0 that assigns each edge a weight which we assume here to be non-negative.

The final detection-weight map for visual secret sharing is shown by a test set in Fig. 12. Fig. 11 Flow chart of secret object detection-weight map generation Fig. 12 Weight maps of the final secret object detection.

The obtained dendrite weight mapping error was 0.072%.

(b) Weight maps for the corresponding input images.

The evolution of the synaptic weight maps is shown in Fig. 6b.