Convolutional Neural Network (CNN) for gland images classification

An automatic detection of histopathological images has an important role in helping diagnose step. Even, for determining the status of cancer, benign or malignant A conventional way in cancer detection has infirmity like user dependency, the tendency to the incorrect identification and takes more time. Convolutional Neural Network (CNN) is one of the deep learning architecture that can accommodate automatic feature extraction and classification directly. The ability of CNN to extract a feature of an image in depth underlie our research. The research aims to classify the two statuses of cancer on gland images using CNN. The training process for six, eight and ten layers exploited on this research. The accuracy obtained up to 82.98, 81.91 and 89.36 percent for six, eight and ten layers respectively. But in the future, we need to improve the computing time.