Sentence examples for multiple features is from inspiring English sources

A straightforward strategy to handle multiple features is to concatenate all the feature vectors into a single feature vector.

The fusion of multiple features is regarded as a positive step towards the development of extremely ambitious types of iris recognition [17].

The integration of multiple features is important for action categorization and object recognition in videos, because single feature based representation hardly captures imaging variations and individual attributes.

Multiple features are widely used to characterize real-world datasets.

The multiple features are selected using the Sequential Forward Selection (SFS) algorithm.

Extracted multiple features are utilized within a discriminative learning framework for recognizing interactions between people.

In our proposed framework, multiple features are extracted to represent 3D neuron data.

In feature fusion, multiple features are concatenated into a large feature vector and a single HMM model is trained [9].

The multiple features are selected using the sequential forward selection algorithm we called Co-occurrence of LBP (CoLBP).

In the crowd analysis characteristics, the curve and the multiple features are relatively independent, the relative independence between the arc and the multiple features.

Multiple features are common between the existing taxonomies (e.g. collective architecture, environment structure, presence of communication...), while a large number of features is specific to each taxonomy.