Name
Abstract | ||
|---|---|---|
This paper describes the participation of the RECOD group on the ImageCLEF 2011 Medical Modality Classication sub-task. We present an approach based on genetic programming and kNN for image classication. In our approach the genetic programming is used for the learning of good functions for the combination of similarities obtained from a set of global descriptors for dierent visual evidences such as color, texture, and shape. For each class of the dataset a combination function was learned and used as a kNN classier. Final classication results were generated by a majority voting scheme with the voting functions from each class. Preliminary experiments have shown a good eectiveness of |
Year | Venue | Field |
|---|---|---|
2011 | CLEF (Notebook Papers/Labs/Workshop) | Voting,Genetic programming,Artificial intelligence,Majority rule,Machine learning,Mathematics |
DocType | Citations | PageRank |
Conference | 5 | 0.53 |
References | Authors | |
12 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fabio A. Faria | 1 | 77 | 8.76 |
| Rodrigo Tripodi Calumby | 2 | 61 | 7.75 |
| Ricardo da Silva Torres | 3 | 787 | 61.46 |