Comparative Performance Analysis of Deep Learning Architectures for Oral Cancer Detection Using Histopathological Images
Early and accurate detection of oral cancer is critical for improving patient outcomes. This study presents a comprehensive comparison of five convolutional neural network architectures—MobileNetV2, Xception, VGG19, ResNet50, and DenseNet201—for automated oral cancer detection from histopathological images. All models...