HQNet: An Efficient Convolutional Neural Network for Cervical Cancer Classification
Yang Han, Teoh Teik Toe · 2022
With the rapid development of artificial intelligence, cancer cell classification recognition is also gradually intelligent. Although the classification and recognition methods for some common cancers are mature, Cervical Cancer, as a common cancer among middle- aged women, is often neglected in diagnosis because of the low incidence of malignant tumors. In recent years, the incidence of Cervical Cancer has been increasing year by year and has also gained attention. In this paper, an efficient deformable convolu- tional neural network system(HQNet) was constructed to identify Cervical Cancer cells with different degrees of development.