Research Article
Nonnegative Matrix Factorizations Performing Object Detection and Localization
Table 2
Algorithm performances in terms of and when applied to CarData with factor ranks and . Bold fonts indicate the highest values of precision and recall.
| | Method | | | | | F-measure |
| NMF | 103 | 67 | 0.52 | 0.61 | 0.56 | LNMF | 92 | 78 | 0.46 | 0.54 | 0.5 | NMFsc | 106 | 64 | 0.53 | 0.62 | 0.57 | DLPP | 37 | 133 | 0.19 | 0.22 | 0.2 |
| | Method | | | | | F-measure |
| NMF | 112 | 58 | 0.56 | 0.66 | 0.61 | LNMF | 86 | 85 | 0.43 | 0.5 | 0.46 | NMFsc | 110 | 60 | 0.55 | 0.65 | 0.59 | DLPP | 21 | 93 | 0.11 | 0.18 | 0.13 |
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