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- W2891686988 abstract "Deep Learning has already shown power in many application fields, and is accepted by more and more people as a better approach than the traditional machine learning models. In particular, the implementation of deep learning algorithms, especially Convolutional Neural Networks (CNN), brings huge benefits to the medical field, where a huge number of images are to be processed and analyzed. This paper aims to develop a deep learning model to address the blood cell classification problem, which is one of the most challenging problems in blood diagnosis. A CNN-based framework is built to automatically classify the blood cell images into subtypes of the cells. Experiments are conducted on a dataset of 13k images of blood cells with their subtypes, and the results show that our proposed model provide better results in terms of evaluation parameters." @default.
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- W2891686988 date "2018-12-01" @default.
- W2891686988 modified "2023-10-16" @default.
- W2891686988 title "Detection of subtype blood cells using deep learning" @default.
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- W2891686988 doi "https://doi.org/10.1016/j.cogsys.2018.08.022" @default.
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