Special Libraries, December 1964

Volume 55, Issue 10https://scholarworks.sjsu.edu/sla_sl_1964/1009/thumbnail.jp

Special Libraries, December 1964

Volume 55, Issue 10https://scholarworks.sjsu.edu/sla_sl_1964/1009/thumbnail.jp

Special Libraries, January 1966

Volume 57, Issue 1https://scholarworks.sjsu.edu/sla_sl_1966/1000/thumbnail.jp

Searching the social science literature on water: a guide to selecter information storage and retrieval systems - preliminary version

Submitted to Water Resources Scientific Information Center, supported jointly by the Office of Water Resources Research, U.S. Department of the Interior, and by Colorado State University.Grant agreement Number 14-31-0001-3183

Special Libraries, September 1957

Volume 48, Issue 7https://scholarworks.sjsu.edu/sla_sl_1957/1006/thumbnail.jp

Special Libraries, December 1966

Volume 57, Issue 10https://scholarworks.sjsu.edu/sla_sl_1966/1009/thumbnail.jp

Special Libraries, January 1967

Volume 58, Issue 1https://scholarworks.sjsu.edu/sla_sl_1967/1000/thumbnail.jp

Technology transfer - A selected bibliography

Selected bibliography on technology transfe

Saliency for Image Description and Retrieval

We live in a world where we are surrounded by ever increasing numbers of images. More often than not, these images have very little metadata by which they can be indexed and searched. In order to avoid information overload, techniques need to be developed to enable these image collections to be searched by their content. Much of the previous work on image retrieval has used global features such as colour and texture to describe the content of the image. However, these global features are insufficient to accurately describe the image content when different parts of the image have different characteristics. This thesis initially discusses how this problem can be circumvented by using salient interest regions to select the areas of the image that are most interesting and generate local descriptors to describe the image characteristics in that region. The thesis discusses a number of different saliency detectors that are suitable for robust retrieval purposes and performs a comparison between a number of these region detectors. The thesis then discusses how salient regions can be used for image retrieval using a number of techniques, but most importantly, two techniques inspired from the field of textual information retrieval. Using these robust retrieval techniques, a new paradigm in image retrieval is discussed, whereby the retrieval takes place on a mobile device using a query image captured by a built-in camera. This paradigm is demonstrated in the context of an art gallery, in which the device can be used to find more information about particular images. The final chapter of the thesis discusses some approaches to bridging the semantic gap in image retrieval. The chapter explores ways in which un-annotated image collections can be searched by keyword. Two techniques are discussed; the first explicitly attempts to automatically annotate the un-annotated images so that the automatically applied annotations can be used for searching. The second approach does not try to explicitly annotate images, but rather, through the use of linear algebra, it attempts to create a semantic space in which images and keywords are positioned such that images are close to the keywords that represent them within the space