In this paper, we first apply the theory of wallpaper groups to natural images and extract a novel feature to depict the symmetry property of natural images. The original proposed...
Active learning methods have been considered with an increasing interest in the content-based image retrieval (CBIR) community. In this article, we propose an efficient method bas...
Abstract-- This paper presents a novel approach using combined features to retrieve images containing specific objects, scenes or buildings. The content of an image is characterize...
Content-based image retrieval systems still have difficulties to bridge the semantic gap between the low-level representation of images and the high level concepts the user is loo...
Active learning methods have been considered with an increased interest in the content-based image retrieval (CBIR) community. Those methods used to be based on classical classifi...
Content-based image retrieval has become an indispensable tool for managing the rapidly growing collections of digital images. The goal is to organize the contents semantically, a...
Dejan Depalov, Thrasyvoulos N. Pappas, Dongge Li, ...
The automatic computation of features for content-based image retrieval still has difficulties to represent the concepts the user has in mind. Whenever an additional learning stra...
Querying by Visual Thesaurus (VT) is a novel paradigm for content-based image retrieval approaches for it gives the user the possibility, in case of inappropriate starting example...
Methods of retrieving images that incorporate humangenerated metadata, such as keyword annotation and collaborative filtering, are less vulnerable to the semantic gap than content...
Abstract. The ability to learn from user interaction is an important asset for content-based image retrieval (CBIR) systems. Over short times scales, it enables the integration of ...