Abstract
This paper proposes a method to diagnose atopic dermatitis based on deep learning network by analyzing image data of infected skin areas. We use deep learning network to analyze the layers and get the suitable layer for diseased and non-diseased images. These images are further feature extracted through HOG feature extraction and SVM classifier to classify disease and non-disease. The proposed method proves to be effective in precision and recall, that can be considered as an adjunct to traditional diagnostic methods, and the results obtained are equivalent to that of a diagnostician while limiting the heterogeneity between the predictors.
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Nguyen, AM., Vu, VH., Trinh, TB. (2023). Detection and Diagnosis of Atopic Dermatitis Using Deep Learning Network. In: Nguyen, T.D.L., Verdú, E., Le, A.N., Ganzha, M. (eds) Intelligent Systems and Networks. ICISN 2023. Lecture Notes in Networks and Systems, vol 752. Springer, Singapore. https://doi.org/10.1007/978-981-99-4725-6_19
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DOI: https://doi.org/10.1007/978-981-99-4725-6_19
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