Deep learning techniques have led to remarkable breakthroughs in the field of object
detection and have spawned a lot of scene-understanding tasks in recent years. Scene …

We have recently observed a convergence of technologies to foster the emergence of
lifelogging as a mainstream activity. Computer storage has become significantly cheaper …

Convolutional neural network (CNN) gained great attention for robust feature extraction and
information mining. CNN had been used for variety of applications such as object …

We have witnessed great interest and a wealth of promise in content-based image retrieval
as an emerging technology. While the last decade laid foundation to such promise, it also …

Aesthetics, in the world of art and photography, refers to the principles of the nature and
appreciation of beauty. Judging beauty and other aesthetic qualities of photographs is a …

Extending beyond the boundaries of science, art, and culture, content-based multimedia
information retrieval provides new paradigms and methods for searching through the myriad …

Recent image retrieval techniques are focusing on multiple image features for the efficient
image retrieval. It has been an inevitable requirement to fetch the images from a variety of …

Nowadays, more and more images are available. However, to find a required image for an
ordinary user is a challenging task. Large amount of researches on image retrieval have …

Multiple-instance problems arise from the situations where training class labels are attached
to sets of samples (named bags), instead of individual samples within each bag (called …

A probabilistic formulation for semantic image annotation and retrieval is proposed.
Annotation and retrieval are posed as classification problems where each class is defined …