G. Arutperumjothi1,*, K. Suganya Devi2, C. Rani3, P. Srinivasan4
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1069-1086, 2023, DOI:10.32604/iasc.2023.028423
Abstract In recent years, Peripheral blood smear is a generic analysis to assess the person’s health status. Manual testing of Peripheral blood smear images are difficult, time-consuming and is subject to human intervention and visual error. This method encouraged for researchers to present algorithms and techniques to perform the peripheral blood smear analysis with the help of computer-assisted and decision-making techniques. Existing CAD based methods are lacks in attaining the accurate detection of abnormalities present in the images. In order to mitigate this issue Deep Convolution Neural Network (DCNN) based automatic classification technique is introduced with the classification of eight groups… More >
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