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. 2022 Jan 3;9:813996. doi: 10.3389/fcell.2021.813996

TABLE 3.

Other proposed models.

Proposed individual model (Abbreviation) Meaning Training
ResNet-18-RVFL (BCRRNet) We select RVFL to substitute the end four layers of the trained transferred ResNet-18 and get BCRRNet. RVFL in the BCRRNet is trained by the features which are extracted from FC256.
ResNet-18-ELM (BCRENet) We select ELM to substitute the end four layers of the trained transferred ResNet-18 and get BCRENet. ELM in the BCRENet is trained by the features which are extracted from FC256.
ResNet-18-SNN (BCRSNet) We select SNN to substitute the end four layers of the trained transferred ResNet-18 and get BCRSNet. SNN in the BCRSNet is trained by the features which are extracted from FC256.
Proposed ensemble model (Abbreviation) Meaning Training
 AlexNet-RNNs-En (BCARENet) The pre-trained AlexNet is the backbone of the BCARENet and the results of the BCARENet are generated by the ensemble of the predictions from the three RNNs by the majority voting. The trained transferred AlexNet is obtained by training the transferred AlexNet on the processed training blood cell data set. Then, three RNNs in the BCARENet are trained by the features which are extracted from FC256.
 ResNet-50-RNNs-En (BCR5RENet) The pre-trained ResNet-50 is the backbone of the BCR5RENet and the results of the BCR5RENet are generated by the ensemble of the predictions from the three RNNs by the majority voting. The trained transferred ResNet-50 is obtained by training the pre-trained ResNet-50 on the processed training blood cell data set. Then, three RNNs in the BCR5RENet are trained by the features which are extracted from FC256.
 MobileNet-V2-RNNs-En (BCMV2RENet) The pre-trained MobileNet-V2 is the backbone of the BCMV2RENet and the results of the BCMV2RENet are generated by the ensemble of the predictions from the three RNNs by the majority voting. The trained transferred MobileNet-V2 is obtained by training the pre-trained MobileNet-V2 on the processed training blood cell data set. Then, three RNNs in the BCMV2RENet are trained by the features which are extracted from FC256.