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Fig 1.

Fish freshness dataset sample images (a) anchovy (b) horse mackerel.

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Fig 1 Expand

Fig 2.

Proposed hybrid model structure.

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Fig 2 Expand

Table 1.

Image counts of the training, testing, and validation dataset.

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Table 1 Expand

Table 2.

Models training parameters.

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Table 2 Expand

Table 3.

Yolo-v5 loss and avg loss values.

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Table 3 Expand

Fig 3.

(a) Training-test accuracy, (b) Loss plots of models using Dataset1.

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Fig 3 Expand

Fig 4.

(a) Training-test accuracy, (b) Loss plots of models using Dataset2.

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Fig 4 Expand

Table 4.

Test results obtained from model structures using the training-test dataset.

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Table 4 Expand

Fig 5.

Confusion matrix results from (a) Inception-ResNet-v2, (b) Xception model structures using the validation dataset in Dataset1.

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Fig 5 Expand

Fig 6.

Confusion matrix results from (a) Inception-ResNet-v2, (b) Xception model structures using the validation dataset in Dataset2.

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Fig 6 Expand

Table 5.

Test results from model structures using the validation dataset.

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Table 5 Expand

Fig 7.

Proposed hybrid model structure performance diagram.

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Fig 7 Expand

Table 6.

Performance test results of the proposed hybrid model.

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Table 6 Expand

Fig 8.

Sample images of the performance test (a) anchovy, (b) horse mackerel.

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Fig 8 Expand

Table 7.

Comparison of proposed hybrid model constructs with existing methods to detect fish freshness.

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Table 7 Expand