Supervised methods have been widely used for image classifications. Although great
progress has been made, existing supervised methods rely on well-labeled samples for …

Different views represent different aspects of images. It is more effective to combine them for
visual classifications. This paper proposes a novel multiview label sharing method to …

Accurately classifying images using few-shot samples have been widely explored by
researchers. However, these methods have two drawbacks. First, images are often used …

Image retrieval procedures locate interest points and consider the features as the visual
property of an image in computer vision. These primitive features define visual attributes as …

Due to the rapid advancements of sensory and computing technology, multi-modal data
sources that represent the same pattern or phenomenon have attracted growing attention …

The bag-of-visual-words model is widely used for visual content analysis. For visual data,
the codebook plays an important role for efficient representation. However, the codebook …

The categorization accuracies of objects have been greatly improved in recent years.
However, large quantities of labeled images are needed. many methods fail when only few …

Image classification methods often use class-level information without considering the
distinctive character of each image. Images of the same class may have varied …

Pore-based fingerprint recognition has become more attractive in recent years because of its
uniqueness and difficulty in forgeability. However, most of the existing methods use pore …

Due to interclass and intraclass variations, the images of different classes are often cluttered
which makes it hard for efficient classifications. The use of discriminative classification …