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 …

Automated annotation of digital pictures has been a highly challenging problem for
computer scientists since the invention of computers. The capability of annotating pictures by …

The last decade has witnessed great interest in research on content-based image retrieval.
This has paved the way for a large number of new techniques and systems, and a growing …

Active learning is a machine learning technique that selects the most informative samples for
labeling and uses them as training data. It has been widely explored in multimedia research …

A comprehensive survey on patch recognition, which is a crucial part of content-based
image retrieval (CBIR), is presented. CBIR can be viewed as a methodology in which three …

Content-based image retrieval (CBIR), which is aimed to search images from a large size
image database based on visual contents of images in an efficient and accurate way as per …

User interaction is an effective way to handle the semantic gap problem in image annotation.
To minimize user effort in the interactions, many active learning methods were proposed …

In content-based image retrieval, relevance feedback is studied extensively to narrow the
gap between low-level image feature and high-level semantic concept. However, most …

Efficient and effective use of renewable energy, distributed generation and energy storage
can potentially solve global problems such as energy crisis and climate change. A promising …

High retrieval precision in content-based image retrieval can be attained by adopting
relevance feedback mechanisms. These mechanisms require that the user judges the …