A Deep Learning Approach to Enhance Semantic Segmentation of Bacteria and Pus Cells from Microscopic Urine Smear Images Using Synthetic Data
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-58181-6_21
Reference21 articles.
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3. Yan, M., Liu, Q., Yin, Z., Wang, D. Liang, Y.: A bidirectional context propagation network for urine sediment particle detection in microscopic images. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 981–985 (2020). https://doi.org/10.1109/ICASSP40776.2020.9054367
4. Hiremath P.S., Parashuram, B., Geeta, S.: Automated identification and classification of white blood cells (leukocytes) in digital microscopic images. Int. J. Comput. Appl. (2010)
5. Ahmed, T., Wahid, M.F., Hasan, M.J.: Combining deep convolutional neural network with support vector machine to classify microscopic bacteria images. In: 2019 International Conference on Electrical, Computer and Communication Engineering(ECCE), pp. 1-5 (2019). https://doi.org/10.1109/ECACE.2019.8679397
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