Sentence examples for feature pooling from inspiring English sources

These stages are measurement of a physical quantity relevant for visual quality, also called as feature, pooling the measured data over space and/or time, and mapping the pooled data to an estimate of perceived quality.

In this architecture, principal component analysis (PCA) is used in two convolutional layers, followed by binary hashing in the non-linear layer and block-wise histograms in the feature pooling layer.

For modeling spatiotemporal layout information embedded in facial expressions to improve recognition performance, we extend the idea of spatial pyramid matching (SPM) into video case, and perform spatiotemporal pyramid feature pooling following sparse coding feature extraction.

In this paper, we propose a novel spatial pooling method within an unsupervised feature learning framework, named Rich and Robust Feature Pooling (R2FP), to better extract rich and robust representation from sparse feature maps learned from the raw data.

The first class of models do not use PDs but involve complex image-based computing that includes feature extraction, feature pooling, and normalization [23], [24].

Firstly, an algorithm for computing the Haar-like feature pool on a 32 × 32 grayscale image patch by using all simple and rotated Haar-like prototypes is introduced to represent a vehicle's appearance.

Then, sequential clustering is carried out on all features to give a feature pool.

We repeat the same procedure for all training samples in class c to create the feature pool F q c.

For each f′ i, x2-distance is calculated between the average SIFT feature vector c i. Suppose fmin in the feature pool has the smallest distance to f′ i.

To start, a training sample from class c with all its features F = {f i } is randomly selected and added to the feature pool.

While creating feature pool, we also keep record of the percentage of sample images that contributed to feature f i which is denoted by r i.