Research Article
Breast Cancer Classification from Mammogram Images Using Extreme Learning Machine-Based DenseNet121 Model
Table 1
Comparison accuracies for proposed work and previous research.
| | Reference | Dataset used | Model | Accuracy in % |
| | Abunasser et al., [14] | Kaggel | Xception | 98.59% | | Houssein et al., [15] | DDSM | IMPA-ResNet50 | 98.32% | | Nawaz et al., [16] | BreakHis dataset | DenseNet | 95.4% | | Khan et al., [17] | CBIS-DDSM | ResNet50 | 88% | | Hameed et al., [18] | MIFLUDAN project | Xception | 97.33% | | Joseph et al., [19] | BreakHis dataset | DNN | 96.84% | | Alkassar et al., [20] | BreakHis | DenseNet and Xception | 99% | | Our proposed method | Kaggle dataset | DenseNet121+ELM | 99.47% |
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