Titlebook: Recent Advances in Visual Information Systems; 5th International Co Shi-Kuo Chang,Zen Chen,Suh-Yin Lee Conference proceedings 2002 Springer

Orthosis

書目名稱Recent Advances in Visual Information Systems影響因子(影響力)




書目名稱Recent Advances in Visual Information Systems影響因子(影響力)學(xué)科排名




書目名稱Recent Advances in Visual Information Systems網(wǎng)絡(luò)公開度




書目名稱Recent Advances in Visual Information Systems網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Recent Advances in Visual Information Systems被引頻次




書目名稱Recent Advances in Visual Information Systems被引頻次學(xué)科排名




書目名稱Recent Advances in Visual Information Systems年度引用




書目名稱Recent Advances in Visual Information Systems年度引用學(xué)科排名




書目名稱Recent Advances in Visual Information Systems讀者反饋




書目名稱Recent Advances in Visual Information Systems讀者反饋學(xué)科排名

verdict

卜聞

Multi-sensor Information Fusion by Query Refinementeedback information to the other sensors. The approach is also applicable to evolutionary queries that change in time and/or space, depending upon the temporal/spatial coordinates of the query originator.

涂掉

壓倒性勝利

隼鷹

MiCRoM: A Metric Distance to Compare Segmented Imagesented and represented as a set of regions, and the distance between images is computed according to the visual features of their regions. A major problem of existing distance functions used to compare segmented images is that they are not metrics. Hence, it is not possible to exploit filtering techn

Detonate

Image Retrieval by Regions: Coarse Segmentation and Fine Color Descriptionterest regardless their background in images. The definition of regions in thousands of generic images is a difficult key point, since it should not need user interaction for each image, and nevertheless be as close as possible to regions of interest (to the user). In this paper we first propose a n

CROAK

Fast Approximate Nearest-Neighbor Queries in Metric Feature Spaces by Buoy Indexing to break the “dimensionality curse”. The basis for the proposed method is the partitioning of the feature dataset into a fixed number of clusters that are represented by single buoys. Upon submission of a query request, only a small number of clusters whose buoys are close to the query object are c

發(fā)怨言

ironic

Region-Based Image Retrieval Using Multiple-Features technique that utilizes the regional properties of the images. After image segmentation, each region is represented by its colour, shape, size, and spatial position. Regions of different images are matched and a distance measure between the whole images is calculated. The relative importance of the