Leukocyte Recognition Using a Modified AlexNet and Image to Image GAN Data Augmentation
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-33783-3_13
Reference18 articles.
1. Hegde, R.B., Prasad, K., Hebbar, H., Singh, B.M.K.: Feature extraction using traditional image processing and convolutional neural network methods to classify white blood cells: a study. Australas. Phys. Eng. Sci. Med. 42(2), 627–638 (2019). https://doi.org/10.1007/s13246-019-00742-9
2. Çınar, A., Tuncer, S.A.: Classification of lymphocytes, monocytes, eosinophils, and neutrophils on white blood cells using hybrid Alexnet-GoogleNet-SVM. SN Appl. Sci. 3(4), 1–11 (2021). https://doi.org/10.1007/s42452-021-04485-9
3. Huang, P., et al.: Attention-aware residual network based manifold learning for white blood cells classification. IEEE J. Biomed. Health Inform. 25(4), 1206–1214 (2021). https://doi.org/10.1109/JBHI.2020.3012711
4. Ghosh, S., Majumder, M., Kudeshia, A.: LeukoX: leukocyte classification using least entropy combiner (LEC) for ensemble learning. IEEE Trans. Circuits Syst. II Express Briefs 68(8), 2977–2981 (2021). https://doi.org/10.1109/TCSII.2021.3064389
5. Chen, H., et al.: Accurate classification of white blood cells by coupling pre-trained ResNet and DenseNet with SCAM mechanism. BMC Bioinf. 23(1), 1–20 (2022). https://doi.org/10.1186/S12859-022-04824-6/FIGURES/10
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