Name
Abstract | ||
|---|---|---|
This paper presents Blackthorn, an efficient interactive multimodal learning approach facilitating analysis of multimedia collections of up to 100 million items on a single high-end workstation. Blackthorn features efficient data compression, feature selection, and optimizations to the interactive learning process. The Ratio-64 data representation introduced in this paper only costs tens of bytes ... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TMM.2017.2755986 | IEEE Transactions on Multimedia |
Keywords | Field | DocType |
Multimedia communication,Semantics,Visualization,Quantization (signal),Data compression,Data models | Data modeling,Interactive Learning,Relevance feedback,External Data Representation,Pattern recognition,Feature selection,Visualization,Computer science,Artificial intelligence,Data compression,Multimodal learning,Machine learning | Journal |
Volume | Issue | ISSN |
20 | 3 | 1520-9210 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jan Zahálka | 1 | 34 | 8.80 |
| Stevan Rudinac | 2 | 188 | 20.45 |
| Björn Þór Jónsson | 3 | 565 | 60.38 |
| Dennis C. Koelma | 4 | 57 | 4.65 |
| Marcel Worring | 5 | 6439 | 384.88 |