Research Article
Using Machine Learning Approaches for Food Quality Detection
Table 4
Evaluation index of surveyed articles.
| Method | Classification number | Data types | Precision (%) | Recall (%) | F1 score (%) |
| [28] | 2 | Hyperspectral imaging | 83.3 | | | [29] | 2 | Hyperspectral imaging | 91.6 | | | [30] | 2 | Hyperspectral imaging | 93.3 | | | [31] | 2 | RGB image | 91–97 | | | [10] | 2 | Hyperspectral imaging | 88.14 | | 89.28 | [11] | 2 | Spectroscopy | | | 89 | [15] | 2 | RGB image | 97 | | | [32] | 2 | RGB image | 90 | | | [33] | 2 | Laser backscattering | 92.5 | | | [19] | 2 | Spectroscopic images | 97.3 | | | [34] | 2 | RGB image | 92 | | | [35] | 2 | RGB image | 87.27 | | | [19] | 2 | RGB image | 65–96.5 | | | [36] | 2 | RGB image | 97.5 | | | ResNets | 3 | Infrared video | 97.53 | 97.50 | 97.51 | ResNets | 18 | RGB image | 95.69 | 94.72 | 95.07 | DenseNets | 3 | RGB image | 97.73 | 97.69 | 97.7 | DenseNets | 18 | RGB image | 95.55 | 94.73 | 95 |
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