Name
Abstract | ||
|---|---|---|
Online auctions have become extremely popular in recent years. Ability to predict winning bid prices accurately can help bidders to maximize their profit. This paper proposes a number of strategies and algorithms for performing such predictions for the ... |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/CIMCA.2008.45 | CIMCA/IAWTIC/ISE |
Keywords | Field | DocType |
online auction,classifier training,online image,human-machine interaction,recent year,bid price,production,human computer interaction,inspection,level of detail,computer vision,accuracy,machine learning,real time,image classification,data mining,learning artificial intelligence,production process,machine vision | Image classifier,Data set,Machine vision,Computer science,Level of detail,Scheduling (production processes),Artificial intelligence,Contextual image classification,Online adaptation,Machine learning,Human machine interaction | Conference |
Citations | PageRank | References |
1 | 0.35 | 11 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Edwin Lughofer | 1 | 1940 | 99.72 |
| Jim Smith | 2 | 50 | 8.91 |
| Praminda Caleb-Solly | 3 | 117 | 17.51 |
| Atif Tahir | 4 | 460 | 27.12 |
| Christian Eitzinger | 5 | 164 | 15.33 |
| Davy Sannen | 6 | 60 | 4.70 |
| Hendrik Van Brussel | 7 | 539 | 67.67 |