IMPROVING THE VISUAL DIAGNOSIS OF DISEASES USING HYBRID NEURAL NETWORKS

Computer recognition algorithms based on microscopic images of blood particles can be used as a decision support mechanism to help specialists speed up the diagnostic process. The purpose of this work is to evaluate the quantitative analysis of hybrid neural networks (CNN + RNN). It can visually check the solution area of the input image used by CNN + LSTM. Based on the microscope image, the recognition results of blood composition particles according to their shape have been achieved up to 90%.

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