Probabilistic feature relevance learning (PFRL) is an effective technique for adaptively computing local feature relevance for content-based image retrieval. It however becomes le...
Abstract. The present work is focused on a global image characterization based on a description of the 2D displacements of the different shapes present in the image, which can be e...
Edoardo Ardizzone, Antonio Chella, Roberto Pirrone
Archeological sites have heterogeneous information ranging from different artifacts, image data, geo-spatial information, chronological data, and other relevant metadata. ETANA-DL,...
Naga Srinivas Vemuri, Ricardo da Silva Torres, Rao...
Feature extraction and similarity measurement are two important operations in content-based image retrieval systems. We optimize and vectorize typical feature extraction algorithm...
Many content-based image retrieval applications suffer from small sample set and high dimensionality problems. Relevance feedback is often used to alleviate those problems. In thi...