Sentence examples for face recognition task from inspiring English sources

Figure 1 shows convolutional neural network for face recognition task.

This indicates that the proposed method can achieve satisfactory accuracy for the face recognition task.

Few papers in the literature are dedicated to the 3D asymmetry face recognition task so far.

Deep learning is proved to give robust image representation for single training sample per person in face recognition task [64].

However, in recent times, most face images that are acquired and are available for face recognition task are color images.

On both the random Gaussian data and the face recognition task, the numerical simulation results illustrate the efficiency of SASR.

Subspace methods have been successfully applied to face recognition tasks.

Basically, in face recognition tasks, the inputs are the original gray-level (intensity) image.

In face recognition tasks, one kind of feature set is not adequate to generate superior results; thus, selection and combination of complementary features are crucial steps.

This work presents a multi-objective wrapper, based on genetic algorithms, to select the most relevant set of features for face recognition tasks.

A small effort has been made for designing a hexagonal sampled SIFT feature descriptor with its applicability in face recognition tasks.