Name
Abstract | ||
|---|---|---|
In the field of big data applications, image information is widely used. The value density of information utilization in big data is very low, and how to extract useful information quickly is very important. So we should transform the unstructured image data source into a form that can be analyzed. In this paper, we proposed a fast image retrieval method which designed for big data. First of all, ... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TII.2017.2657545 | IEEE Transactions on Industrial Informatics |
Keywords | Field | DocType |
Image retrieval,Feature extraction,Image color analysis,Visualization,Shape,Histograms,Image edge detection | Automatic image annotation,Feature detection (computer vision),Pattern recognition,Computer science,Feature (computer vision),Image texture,Image retrieval,Feature extraction,Artificial intelligence,Kanade–Lucas–Tomasi feature tracker,Visual Word | Journal |
Volume | Issue | ISSN |
13 | 5 | 1551-3203 |
Citations | PageRank | References |
6 | 0.46 | 39 |
Authors | ||
5 | ||