… deep convolutional neural net- work based model to classify the cervical cell images for
detecting malignancy… size of the dataset to improve the classification performance. The proposed …

… The experiments are conducted on publicly available datasets, including Routine Colon
Cancer (RCC) classification and detection and the Nuclei Segmentation Challenge 2018 …

… This paper proposes the first microscopic pathological HSI dataset for CC detection, and it
… for cancer detection in the pathological HSI. Up to 880 scenes of microscopic hyperspectral …

… classification scheme for lung cancers presented in microscopic images using a deep
convolutional neural … classification scheme for lung cancers in microscopic images using a DCNN. …

… Tehsin, ‘‘Acute lymphoblastic leukemia detection and classification of its subtypes using
pretrained deep convolutional neural networks,’’ Technol. Cancer Res. Treatment, vol. 17, Jan. …

… major challenge in malignant lung cell classification for cytotechnologists and … classification
of malignant lung cells from microscopic images using a deep convolutional neural network …

… input images are fed directly to the deep model for final decision. In this research, the accuracy
of a new deep convolutional neural network (CNN) for cancer detection is explored. The …

… with a less complex neural network. The current state of art using Inception v3 convolutional
neural network provides classification accuracy of 87.02% [3]. Research on this network has …

… An alternative approach is to use convolutional neural networks (CNNs) to learn the most …
shearlet-based deep neural network method for breast cancer detection and Gleason grading …

… Leukemia is a fatal cancer and has two main types: Acute and chronic. … for diagnosis of all
subtypes of leukemia from microscopic blood cell images using convolutional neural networks (…