Name
Abstract | ||
|---|---|---|
Class imbalance is a common problem in the case of real-world object detection and classification tasks. Data of some classes are abundant, making them an overrepresented majority, and data of other classes are scarce, making them an underrepresented minority. This imbalance makes it challenging for a classifier to appropriately learn the discriminating boundaries of the majority and minority clas... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TNNLS.2017.2732482 | IEEE Transactions on Neural Networks and Learning Systems |
Keywords | Field | DocType |
Training,Australia,Neural networks,Computer vision,Tag clouds,Training data,Testing | Object detection,Data set,Pattern recognition,Computer science,Underrepresented Minority,Tag cloud,Artificial intelligence,Artificial neural network,Contextual image classification,Classifier (linguistics),Machine learning,Binary number | Journal |
Volume | Issue | ISSN |
29 | 8 | 2162-237X |
Citations | PageRank | References |
21 | 0.73 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Salman Khan | 1 | 387 | 41.05 |
| Munawar Hayat | 2 | 315 | 19.30 |
| M. Bennamoun | 3 | 3197 | 167.23 |
| Ferdous Ahmed Sohel | 4 | 623 | 31.78 |
| Roberto Togneri | 5 | 814 | 48.33 |