Sentence examples for more discriminative shape from inspiring English sources

To our best knowledge, this is the first attempt to learn more discriminative shape descriptors and more accurate shape correspondence jointly using the triplet CNNs.

In this paper, in order to obtain more discriminative shape descriptors in an automated fashion, we develop a novel approach to jointly learning shape descriptors and their correspondence in deep triplet convolutional neural networks (CNNs).

Consequently, features that are more discriminative need to be identified before any pattern recognition technique can be applied.

Two versions of Shape Statistic Distribution features are proposed which are derived from Informed Haar-like feature, but more discriminative than the original one.

This result confirms that the features obtained using ART have more discriminative power compared to features obtained using FD, GFD, and RCF. Figure 21 The separability measures comparing the ART, FD, GFD, and RCF shape descriptors.

Heuristics are necessary to guide a narrower, more discriminative search.

Obviously, more concentrated coefficients reveal more discriminative information.

This combination makes the visual words more discriminative.

Then we develop a discriminative shape descriptor for retrieval using many-to-one encoder.

Further, we analyze the development of deeper, thus more discriminative 3D CNNs.

The larger the F-score is, the more likely this feature is more discriminative.