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- W3195138176 abstract "The aim of this research is to develop Deep Convolutional Neural Networks (DCNN) to diagnose the breast cancer using infrared thermal images. Four DCNN models (AlexNet, VGGNet, ResNet50 and GoogleNet) have been evaluated for cancer diagnosis using the Virtual Lab database and they have demonstrated their high performance in terms of medical image classification. The binary decision corresponds to two classes: malignant cancer and benign cancer. We have found that the considered DCNNs are providing very good accuracy in the breast cancer diagnosis using infrared thermography." @default.
- W3195138176 created "2021-08-30" @default.
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- W3195138176 date "2021-07-01" @default.
- W3195138176 modified "2023-10-14" @default.
- W3195138176 title "A Deep CNN Approach Using Thermal Imagery for Breast Cancer Diagnosis" @default.
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- W3195138176 doi "https://doi.org/10.1109/ecai52376.2021.9515189" @default.
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